id stringlengths 7 11 | source stringclasses 1
value | category stringclasses 11
values | title stringlengths 15 214 | text stringlengths 70 30.5k | url stringlengths 57 160 | tags stringlengths 3 113 | created_at int64 1.22B 1.79B |
|---|---|---|---|---|---|---|---|
se_79109487 | stackoverflow | MACHINE_LEARNING | How to check whether an sklearn estimator is a scaler? | How to check whether an sklearn estimator is a scaler?
I'm writing a function that needs to determine whether an object passed to it is an imputer (can check with isinstance(obj, _BaseImputer)), a scaler, or something else.
While all imputers have a common base class that identifies them as imputers, scalers do not. I... | https://stackoverflow.com/questions/79109487/how-to-check-whether-an-sklearn-estimator-is-a-scaler | python, scikit-learn, isinstance | 1,729,504,030 |
se_63922690 | stackoverflow | MACHINE_LEARNING | Decision tree Regressor model get max_depth value of the model with highest accuracy | Decision tree Regressor model get max_depth value of the model with highest accuracy
Build a Decision tree Regressor model from X_train set and Y_train labels, with default parameters. Name the model as dt_reg.
Evaluate the model accuracy on the training data set and print its score.
Evaluate the model accuracy on the... | https://stackoverflow.com/questions/63922690/decision-tree-regressor-model-get-max-depth-value-of-the-model-with-highest-accu | python, machine-learning, scikit-learn, decision-tree | 1,600,268,000 |
se_70862659 | stackoverflow | MACHINE_LEARNING | SVR/SVM output predictions are very similar to each other but far from true value | SVR/SVM output predictions are very similar to each other but far from true value
The main idea is to predict 2 target output, based on input features.
the input features are already scaled using Standardscaler() from sklearn.
size of X_train is (190 x 6), Y_train = (190 x 2). X_test is (20 x 6), Y_test = (20x2)
lin... | https://stackoverflow.com/questions/70862659/svr-svm-output-predictions-are-very-similar-to-each-other-but-far-from-true-valu | python, scikit-learn, linear-regression, svm, gridsearchcv | 1,643,196,163 |
se_79107349 | stackoverflow | MACHINE_LEARNING | ValueError: could not convert string to float: '?' while working with MSE | ValueError: could not convert string to float: '?' while working with MSE
I am using the auto-mpg dataset . I am giving the link of the dataset below:
https://www.kaggle.com/datasets/uciml/autompg-dataset
I am giving the code below:
df = pd.read_csv('data/auto-mpg.csv')
df.head()
df = df.drop('car name', axis... | https://stackoverflow.com/questions/79107349/valueerror-could-not-convert-string-to-float-while-working-with-mse | python, machine-learning, scikit-learn, decision-tree | 1,729,435,784 |
se_34847210 | stackoverflow | MACHINE_LEARNING | What exactly does 'use_idf' do when creating a TfidfTransformer in sklearn? | What exactly does 'use_idf' do when creating a TfidfTransformer in sklearn?
I am using the TfidfTransformer from the sklearn package in Python 2.7.
As I was getting comfortable with the arguments, I became a bit confused about use_idf, as in:
TfidfVectorizer(use_idf=False).fit_transform(<corpus goes here>)... | https://stackoverflow.com/questions/34847210/what-exactly-does-use-idf-do-when-creating-a-tfidftransformer-in-sklearn | python, scikit-learn, tf-idf | 1,453,090,296 |
se_79095468 | stackoverflow | MACHINE_LEARNING | How to pass parameters to this sklearn Cox model in a Pipeline? | How to pass parameters to this sklearn Cox model in a Pipeline?
If I run the following Python code it works well:
target = 'churn'
tranOH = ColumnTransformer([ ('one', OneHotEncoder(drop='first', dtype='int'),
make_column_selector(dtype_include='category', pattern=f"^(?!{target}).*")
) ], remainder='passthrough')
... | https://stackoverflow.com/questions/79095468/how-to-pass-parameters-to-this-sklearn-cox-model-in-a-pipeline | python, scikit-learn, cox-regression, scikit-learn-pipeline | 1,729,105,098 |
se_33204500 | stackoverflow | MACHINE_LEARNING | Pandas - automatically detect date columns **at run time** | Pandas - automatically detect date columns **at run time**
I was wondering if pandas is capable of automatically detecting which columns are datetime objects and read those columns in as dates instead of strings?
I am looking at the api and related stack overflow posts but I can't seem to figure it out.
This is a b... | https://stackoverflow.com/questions/33204500/pandas-automatically-detect-date-columns-at-run-time | python, pandas, scikit-learn | 1,445,211,521 |
se_79086293 | stackoverflow | MACHINE_LEARNING | Gaussian process binary classification: why is the variance with GPy much smaller than with scikit-learn? | Gaussian process binary classification: why is the variance with GPy much smaller than with scikit-learn?
I'm learning about binary classification with Gaussian Processes and I am comparing GPy with scikit-learn on a toy 1D problem inspired by Martin Krasser's blog post. Both implementations (GPy and scikit-learn) see... | https://stackoverflow.com/questions/79086293/gaussian-process-binary-classification-why-is-the-variance-with-gpy-much-smalle | python, machine-learning, scikit-learn, gaussian-process, gpy | 1,728,911,416 |
se_54267745 | stackoverflow | MACHINE_LEARNING | Implementing custom loss function in scikit learn | Implementing custom loss function in scikit learn
I want to implement a custom loss function in scikit learn. I use the following code snippet:
def my_custom_loss_func(y_true,y_pred):
diff3=max((abs(y_true-y_pred))*y_true)
return diff3
score=make_scorer(my_custom_loss_func,greater_ is_better=False)
clf=RandomF... | https://stackoverflow.com/questions/54267745/implementing-custom-loss-function-in-scikit-learn | python, machine-learning, scikit-learn, data-science, gridsearchcv | 1,547,905,667 |
se_78636029 | stackoverflow | MACHINE_LEARNING | Plot a decision tree from HistGratientBoostingClassifier | Plot a decision tree from HistGratientBoostingClassifier
I have a HistGradientBoostingClassifier model and I want to plot one or more of its decision trees, nevertheless I can't manage to find a native function to do it, I can access the Tree predictor objects and thus it's nodes, but in order to plot it into the skle... | https://stackoverflow.com/questions/78636029/plot-a-decision-tree-from-histgratientboostingclassifier | python, machine-learning, scikit-learn, classification, decision-tree | 1,718,695,594 |
se_34649969 | stackoverflow | MACHINE_LEARNING | How to find the features names of the coefficients using scikit linear regression? | How to find the features names of the coefficients using scikit linear regression?
I use scikit linear regression and if I change the order of the features, the coef are still printed in the same order, hence I would like to know the mapping of the feature with the coeff.
#training the model
model_1_features = ['sqft_... | https://stackoverflow.com/questions/34649969/how-to-find-the-features-names-of-the-coefficients-using-scikit-linear-regressio | python, machine-learning, scikit-learn, linear-regression | 1,452,153,484 |
se_79093729 | stackoverflow | MACHINE_LEARNING | Why does mean prediction go flat after more data points are added in Gaussian Process Regressor | Why does mean prediction go flat after more data points are added in Gaussian Process Regressor
Im trying to do a Bayesian optimization in a robot simulator to find optimal Kd and Kp values that fit a desired trajectory (Sinusoidal motion). First I make some random movements of the arm using random Kp and Kd values wi... | https://stackoverflow.com/questions/79093729/why-does-mean-prediction-go-flat-after-more-data-points-are-added-in-gaussian-pr | python, scikit-learn, gaussian-process | 1,729,076,343 |
se_18306416 | stackoverflow | MACHINE_LEARNING | AdaBoostClassifier with different base learners | AdaBoostClassifier with different base learners
I am trying to use AdaBoostClassifier with a base learner other than DecisionTree. I have tried SVM and KNeighborsClassifier but I get errors. What are the classifiers that can be used with AdaBoostClassifier? | https://stackoverflow.com/questions/18306416/adaboostclassifier-with-different-base-learners | machine-learning, scikit-learn, adaboost | 1,376,886,685 |
se_79090407 | stackoverflow | MACHINE_LEARNING | Is it normal for a class in multiclass SVM to have nearly all data points as support vectors? | Is it normal for a class in multiclass SVM to have nearly all data points as support vectors?
I’m using scikit-learn’s SVC for multiclass classification of the iris dataset and one class has almost all its data points as support vectors. Is this expected, or could there be an issue with my implementation or parameter ... | https://stackoverflow.com/questions/79090407/is-it-normal-for-a-class-in-multiclass-svm-to-have-nearly-all-data-points-as-sup | python, machine-learning, scikit-learn, classification, svm | 1,729,002,511 |
se_62240050 | stackoverflow | MACHINE_LEARNING | How to run model on new data that requires pd.get_dummies? | How to run model on new data that requires pd.get_dummies?
I have a model that runs the following:
import pandas as pd
import numpy as np
# initialize list of lists
data = [['tom', 10,1,'a'], ['tom', 15,5,'a'], ['tom', 14,1,'a'], ['tom', 15,4,'b'], ['tom', 18,1,'b'], ['tom', 15,6,'a'], ['tom', 17,3,'a']
, ['t... | https://stackoverflow.com/questions/62240050/how-to-run-model-on-new-data-that-requires-pd-get-dummies | python, pandas, scikit-learn | 1,591,495,166 |
se_29788047 | stackoverflow | MACHINE_LEARNING | Keep TFIDF result for predicting new content | Keep TFIDF result for predicting new content
I am using sklearn on Python to do some clustering. I've trained 200,000 data, and code below works well.
corpus = open("token_from_xml.txt")
vectorizer = CountVectorizer(decode_error="replace")
transformer = TfidfTransformer()
tfidf = transformer.fit_transform(vectorizer.f... | https://stackoverflow.com/questions/29788047/keep-tfidf-result-for-predicting-new-content | python, machine-learning, scikit-learn, tf-idf | 1,429,678,506 |
se_45044225 | stackoverflow | MACHINE_LEARNING | Splitting data to training and testing | Splitting data to training and testing
Does anyone know how can I train on one dataset and test on another dataset?
So far I only know we can split one dataset into training and testing with this line of code:
X_train, X_test, y_train, y_test = \
train_test_split(X, y, test_size=0.30, random_state=1)
I don... | https://stackoverflow.com/questions/45044225/splitting-data-to-training-and-testing | split, scikit-learn, training-data | 1,499,806,110 |
se_79063665 | stackoverflow | MACHINE_LEARNING | python non-linear regressor for incremental learning | python non-linear regressor for incremental learning
I'm wondering if there is a non-linear regression routine with scikit-learn which allows for incremental learning, ie though the partial_fit call. I see that SGDRegressor and PassiveAggressiveRegressor both allow partial_fit, but are linear, and my data is decidedly... | https://stackoverflow.com/questions/79063665/python-non-linear-regressor-for-incremental-learning | machine-learning, scikit-learn, non-linear-regression, incremental | 1,728,335,939 |
se_36382572 | stackoverflow | MACHINE_LEARNING | How to apply model trained with PCA and Random Forest to test data? | How to apply model trained with PCA and Random Forest to test data?
In solving one of the machine learning problem, I am implementing PCA on training data and and then applying .transform on train data using sklearn. After observing the variances, I retain only those columns from the transformed data whose variance is... | https://stackoverflow.com/questions/36382572/how-to-apply-model-trained-with-pca-and-random-forest-to-test-data | python-2.7, machine-learning, scikit-learn, random-forest | 1,459,667,221 |
se_20224526 | stackoverflow | MACHINE_LEARNING | How to extract the decision rules from scikit-learn decision-tree? | How to extract the decision rules from scikit-learn decision-tree?
Can I extract the underlying decision-rules (or 'decision paths') from a trained tree in a decision tree as a textual list?
Something like:
if A>0.4 then if B<0.2 then if C>0.8 then class='X' | https://stackoverflow.com/questions/20224526/how-to-extract-the-decision-rules-from-scikit-learn-decision-tree | python, machine-learning, scikit-learn, decision-tree, random-forest | 1,385,488,680 |
se_38519716 | stackoverflow | MACHINE_LEARNING | Scikit-learn SVM digit recognition | Scikit-learn SVM digit recognition
I want to make a program to recognize the digit in an image. I follow the tutorial in scikit learn .
I can train and fit the svm classifier like the following.
First, I import the libraries and dataset
from sklearn import datasets, svm, metrics
digits = datasets.load_digits()
n_samp... | https://stackoverflow.com/questions/38519716/scikit-learn-svm-digit-recognition | python, image, scikit-learn, mnist | 1,469,169,310 |
se_79076968 | stackoverflow | MACHINE_LEARNING | Grid Search gives nan for best_score with LOGO or LOO, not k-fold CV | Grid Search gives nan for best_score with LOGO or LOO, not k-fold CV
I have a nan R2 score problem with grid search.
FDODB=pd.read_excel('Final Training Set for LOGO.xlsx')
array = FDODB.values
X = array[:,2:126]
Y = array[:,1]
Compd = array[:,0]
scaler = StandardScaler()
X = scaler.fit_transform(X)
params = {
'... | https://stackoverflow.com/questions/79076968/grid-search-gives-nan-for-best-score-with-logo-or-loo-not-k-fold-cv | python, machine-learning, scikit-learn, grid-search | 1,728,626,501 |
se_75644384 | stackoverflow | MACHINE_LEARNING | How to solve Error `Axes' object has no attribute 'is_first_col'? | How to solve Error `Axes' object has no attribute 'is_first_col'?
from sklearn.model_selection import train_test_split, cross_val_score, StratifiedKFold
from matplotlib import pyplot
from sklearn.preprocessing import StandardScaler
import pandas as pd
import matplotlib.pyplot as plt
df = pd.read_csv('D:\... | https://stackoverflow.com/questions/75644384/how-to-solve-error-axes-object-has-no-attribute-is-first-col | python, pandas, matplotlib, scikit-learn | 1,678,040,331 |
se_67417292 | stackoverflow | MACHINE_LEARNING | How to Adjust Feature Weights in Random Forest Model? | How to Adjust Feature Weights in Random Forest Model?
I am utilizing Scikit-Learn's Random Forest library, and I wanted to know if it is possible to change the feature weights, so specific features have more impact. I went through the Random Forest documentation, but I only see weight change for classes which I am not... | https://stackoverflow.com/questions/67417292/how-to-adjust-feature-weights-in-random-forest-model | python, machine-learning, scikit-learn, random-forest | 1,620,300,838 |
se_34674797 | stackoverflow | MACHINE_LEARNING | XGBoost XGBClassifier Defaults in Python | XGBoost XGBClassifier Defaults in Python
I am attempting to use XGBoosts classifier to classify some binary data. When I do the simplest thing and just use the defaults (as follows)
clf = xgb.XGBClassifier()
metLearn=CalibratedClassifierCV(clf, method='isotonic', cv=2)
metLearn.fit(train, trainTarget)
testPredictions ... | https://stackoverflow.com/questions/34674797/xgboost-xgbclassifier-defaults-in-python | python, scikit-learn, classification, analytics, xgboost | 1,452,249,037 |
se_71566189 | stackoverflow | MACHINE_LEARNING | Error : All estimators should implement fit and transform, or can be 'drop' or 'passthrough' specifiers when using make_column_transformer | Error : All estimators should implement fit and transform, or can be 'drop' or 'passthrough' specifiers when using make_column_transformer
I am trying to implement a model that uses ColumnTransformer() followed by SVC().
My transform method looks like:
num_features = X_train_svm.select_dtypes(include=n... | https://stackoverflow.com/questions/71566189/error-all-estimators-should-implement-fit-and-transform-or-can-be-drop-or | python, machine-learning, scikit-learn, sklearn-pandas, scikit-learn-pipeline | 1,647,915,201 |
se_79070409 | stackoverflow | MACHINE_LEARNING | How do I pass sklearns train_test_split actual dataseries and not single values as input argument? | How do I pass sklearns train_test_split actual dataseries and not single values as input argument?
I want to train an LSTM-based RNN model for binary classification and for that I wanted to use tensorflow keras model with LSTM layers. In order to do so, I need testing input and output as well as validation input and o... | https://stackoverflow.com/questions/79070409/how-do-i-pass-sklearns-train-test-split-actual-dataseries-and-not-single-values | python, numpy, tensorflow, keras, scikit-learn | 1,728,479,624 |
se_79057824 | stackoverflow | MACHINE_LEARNING | LogisticRegression not returning correct results | LogisticRegression not returning correct results
I am trying to predict a classification using logistic regression, based on training data, for a series of points in testing data.
I am getting an output, without errors, but the results, I am told, are wrong (the incorrect output would be considered an error, but there... | https://stackoverflow.com/questions/79057824/logisticregression-not-returning-correct-results | python, machine-learning, scikit-learn, classification, logistic-regression | 1,728,157,286 |
se_63393253 | stackoverflow | MACHINE_LEARNING | Decision tree with a probability target | Decision tree with a probability target
I'm currently working on a model to predict a probability of fatality once a person is infected with the Corona virus.
I'm using a Dutch dataset with categorical variables: date of infection, fatality or cured, gender, age-group etc.
It was suggested to use a decision tree, whic... | https://stackoverflow.com/questions/63393253/decision-tree-with-a-probability-target | python, scikit-learn, decision-tree | 1,597,314,900 |
se_73013164 | stackoverflow | MACHINE_LEARNING | Sklearn StackingClassifier very slow and inconsistent cpu usage | Sklearn StackingClassifier very slow and inconsistent cpu usage
I've been trying out the StackingClassifier and StackingRegressor from sklearn recently but I've noticed it's always very slow and uses my cpu inefficiently. Let's say (just for the sake of this example) that I want to use StackingClassifier to stack a ra... | https://stackoverflow.com/questions/73013164/sklearn-stackingclassifier-very-slow-and-inconsistent-cpu-usage | python, machine-learning, scikit-learn | 1,658,072,670 |
se_53900675 | stackoverflow | MACHINE_LEARNING | How to impute test data with imputed values of training data with GridSearchCV and sklearn Pipeline | How to impute test data with imputed values of training data with GridSearchCV and sklearn Pipeline
I am trying to improve my submissions for the Kaggle House Prices Competition found here. I'm working with the Iowa data available here.
I'm trying to train and test my model using a sklearn pipeline, cross-validating w... | https://stackoverflow.com/questions/53900675/how-to-impute-test-data-with-imputed-values-of-training-data-with-gridsearchcv-a | python, machine-learning, scikit-learn, xgboost, grid-search | 1,545,530,723 |
se_32494216 | stackoverflow | MACHINE_LEARNING | How to retrieve the Hessian after a logistic regression in scikit-learn? | How to retrieve the Hessian after a logistic regression in scikit-learn?
I am using the package scikit-learn to compute a logistic regression on a moderately large data set (300k rows, 2k cols. That's pretty large to me!).
Now, since scikit-learn does not produce confidence intervals, I am calculating them myself. T... | https://stackoverflow.com/questions/32494216/how-to-retrieve-the-hessian-after-a-logistic-regression-in-scikit-learn | scikit-learn, logistic-regression, hessian-matrix | 1,441,864,775 |
se_79061782 | stackoverflow | MACHINE_LEARNING | ImportError: numpy.core.multiarray failed to import with newest numpy version | ImportError: numpy.core.multiarray failed to import with newest numpy version
I am trying to run this code in VSCode and keep running into this error message:
A module that was compiled using NumPy 1.x cannot be run in
NumPy 2.1.2 as it may crash. To support both 1.x and 2.x
versions of NumPy, modules must be compile... | https://stackoverflow.com/questions/79061782/importerror-numpy-core-multiarray-failed-to-import-with-newest-numpy-version | python, numpy, scikit-learn | 1,728,301,219 |
se_51968669 | stackoverflow | MACHINE_LEARNING | Predict() with sklearn LogisticRegression and RandomForest models always predict minority class (1) | Predict() with sklearn LogisticRegression and RandomForest models always predict minority class (1)
I'm building a Logistic Regression model to predict if a transaction is valid (1) or not (0) with a dataset of just 150 observations. My data is distributed as follows between the two classes:
106 observations are 0 (n... | https://stackoverflow.com/questions/51968669/predict-with-sklearn-logisticregression-and-randomforest-models-always-predict | python, machine-learning, scikit-learn, logistic-regression | 1,534,946,632 |
se_46694664 | stackoverflow | MACHINE_LEARNING | Prediction using sklearn's RandomForestRegressor | Prediction using sklearn's RandomForestRegressor
Here's what my data looks like...
date,locale,category,site,alexa_rank,sessions,user_logins
20170110,US,1,google,1,500,5000
20170110,EU,1,google,2,400,2000
20170111,US,2,facebook,2,400,2000
... and so on. This is just a toy dataset I came up with, but which resembl... | https://stackoverflow.com/questions/46694664/prediction-using-sklearns-randomforestregressor | machine-learning, scikit-learn, regression, random-forest | 1,507,744,537 |
se_74250634 | stackoverflow | MACHINE_LEARNING | Can we perform stratify for linear regression model? | Can we perform stratify for linear regression model?
I wanted to perform stratify method while splitting tran_test_split for linear regression problem.
I know that stratify will perform on classification problems as it excepts 2 or more classes
what to know is there any method or way to perform this method for linear ... | https://stackoverflow.com/questions/74250634/can-we-perform-stratify-for-linear-regression-model | python, scikit-learn, model, linear-regression, train-test-split | 1,667,106,518 |
se_62710093 | stackoverflow | MACHINE_LEARNING | How do I install sklearn module properly? | How do I install sklearn module properly?
I'm trying to install sklearn module using pip command but after the installation is completed , all I can see is this folder
C:\Users\Aditi\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.8_qbz5n2kfra8p0\LocalCache\local-packages\Python38\site-packages\sklearn-0.0-py... | https://stackoverflow.com/questions/62710093/how-do-i-install-sklearn-module-properly | python, scikit-learn, data-science, sklearn-pandas | 1,593,759,652 |
se_19233771 | stackoverflow | MACHINE_LEARNING | sklearn plot confusion matrix with labels | sklearn plot confusion matrix with labels
I want to plot a confusion matrix to visualize the classifer's performance, but it shows only the numbers of the labels, not the labels themselves:
from sklearn.metrics import confusion_matrix
import pylab as pl
y_test=['business', 'business', 'business', 'business', 'busines... | https://stackoverflow.com/questions/19233771/sklearn-plot-confusion-matrix-with-labels | python, matplotlib, scikit-learn | 1,381,176,533 |
se_73479899 | stackoverflow | MACHINE_LEARNING | sklearn can't find lapack in new conda environment | sklearn can't find lapack in new conda environment
Question:
Why can't sklearn detect its liblapack dependency and how do I fix this?
Background:
I the following conda environment (torch-nightly) with scikit-learn installed (note that the liblapack dependency also exists):
(torch-nightly) au@a2 ~ % conda list |gre... | https://stackoverflow.com/questions/73479899/sklearn-cant-find-lapack-in-new-conda-environment | python, numpy, scikit-learn, scipy, lapack | 1,661,378,279 |
se_69847866 | stackoverflow | MACHINE_LEARNING | Can I set a random state for the Complement Naive Bayes? | Can I set a random state for the Complement Naive Bayes?
I note I can set the random state in random forest classifier, but not in Complement Naive Bayes. I get error
TypeError: __init__() got an unexpected keyword argument 'random_state'
I assume this is because naive_bayes is computing the probability of each class... | https://stackoverflow.com/questions/69847866/can-i-set-a-random-state-for-the-complement-naive-bayes | scikit-learn, naivebayes | 1,636,077,425 |
se_79047194 | stackoverflow | MACHINE_LEARNING | How to scale conditionally using sklearn minmaxscaler | How to scale conditionally using sklearn minmaxscaler
I have a column that has positive, 0 and negative values. Rows with 0 values constitute 90% of dataframe. I want to scale this column but without touching 0 value rows. Only those rows that have non zero value should be scaled between -1 to 1 according to the range... | https://stackoverflow.com/questions/79047194/how-to-scale-conditionally-using-sklearn-minmaxscaler | python-3.x, pandas, scikit-learn, scaling | 1,727,879,003 |
se_77927215 | stackoverflow | MACHINE_LEARNING | Understanding scikit learn import variants | Understanding scikit learn import variants
Scikit learn import statements in their tutorials are on the form
from sklearn.decomposition import PCA
Another versions that works is
import sklearn.decomposition
pca = sklearn.decomposition.PCA(n_components = 2)
However
import sklearn
pca = sklearn.decomposition.PCA(n_com... | https://stackoverflow.com/questions/77927215/understanding-scikit-learn-import-variants | python, scikit-learn, python-import | 1,706,879,189 |
se_39662398 | stackoverflow | MACHINE_LEARNING | scikit learn output metrics.classification_report into CSV/tab-delimited format | scikit learn output metrics.classification_report into CSV/tab-delimited format
I'm doing a multiclass text classification in Scikit-Learn. The dataset is being trained using the Multinomial Naive Bayes classifier having hundreds of labels. Here's an extract from the Scikit Learn script for fitting the MNB model
from ... | https://stackoverflow.com/questions/39662398/scikit-learn-output-metrics-classification-report-into-csv-tab-delimited-format | python, csv, text, scikit-learn, classification | 1,474,638,319 |
se_79031928 | stackoverflow | MACHINE_LEARNING | Why does average_precision_score ignore predictions where y_true = 0? | Why does average_precision_score ignore predictions where y_true = 0?
Consider this example:
import numpy as np
from sklearn import metrics
y_true = np.array([[1, 1, 1],[0, 0, 0],[0, 0, 0]])
y_pred = np.array([[1, 1, 1],[.9, .9, .9],[.8, .8, .8]])
aps = metrics.average_precision_score(y_true, y_pred, average='micro'... | https://stackoverflow.com/questions/79031928/why-does-average-precision-score-ignore-predictions-where-y-true-0 | python, scikit-learn | 1,727,449,372 |
se_79043871 | stackoverflow | MACHINE_LEARNING | How to prevent big sklearn random forest model from overloading the CPU core? | How to prevent big sklearn random forest model from overloading the CPU core?
I trained a random forest model with sklearn using RandomizedSearchCV.
I stored the model as a joblib file and now I use it to make forecasts everyday on a server in a docker container.
Basically the process is:
watcher.py:
def watch():
... | https://stackoverflow.com/questions/79043871/how-to-prevent-big-sklearn-random-forest-model-from-overloading-the-cpu-core | python, docker, machine-learning, scikit-learn, parallel-processing | 1,727,797,784 |
se_62541593 | stackoverflow | MACHINE_LEARNING | How to create balanced k-means geospatial clusters? | How to create balanced k-means geospatial clusters?
I have 9000 USA-based points (that are accounts) with a variety of different string and numeric columns/attributes. I'm trying to evenly divide these points/accounts up into equitable groupings that are both spatially grouped as well as weighted (in a gravity sense) ... | https://stackoverflow.com/questions/62541593/how-to-create-balanced-k-means-geospatial-clusters | python, pandas, scikit-learn, cluster-analysis, geospatial | 1,592,937,326 |
se_44932469 | stackoverflow | MACHINE_LEARNING | Optimizer Tuning in sklearn Gaussian Process Regressor | Optimizer Tuning in sklearn Gaussian Process Regressor
I'm attempting to use a GaussianProcessRegressor as part of scikit-learn 0.18.1
I'm training on 200 data points and using 13 input features for my kernel – a constant multiplied by a radial basis function with twelve elements. The model runs without complaints, b... | https://stackoverflow.com/questions/44932469/optimizer-tuning-in-sklearn-gaussian-process-regressor | python, machine-learning, scikit-learn, data-science | 1,499,275,386 |
se_55484101 | stackoverflow | MACHINE_LEARNING | Trying to Find Optimal Price Point in a Data Set | Trying to Find Optimal Price Point in a Data Set
I have a data set that looks like this.
Year Quarter Quantity Price
2000 1 23 142
2000 2 23 144
2000 3 23 147
2000 4 23 151
2001 1 22 160
2001 2 22 183
2001 3 22 186
2001 4 22 186
2002 1 21 212
2002 2 19 ... | https://stackoverflow.com/questions/55484101/trying-to-find-optimal-price-point-in-a-data-set | python, python-3.x, scikit-learn | 1,554,242,095 |
se_79030256 | stackoverflow | MACHINE_LEARNING | How can I achieve accurate imputation of missing values in a dataset? | How can I achieve accurate imputation of missing values in a dataset?
I'm working with a dataset containing details about used cars, and I've encountered several missing values in the Fuel_Type column. The possible values include 'Gasoline', 'E85 Flex Fuel', 'Hybrid', 'Diesel', and others. Currently, my data has over ... | https://stackoverflow.com/questions/79030256/how-can-i-achieve-accurate-imputation-of-missing-values-in-a-dataset | python, pandas, machine-learning, scikit-learn, data-cleaning | 1,727,421,340 |
se_41981441 | stackoverflow | MACHINE_LEARNING | Keep pandas index while applying sklearn | Keep pandas index while applying sklearn
I have a dataset which has a DateTime index and I'm using PCA from sklearn to reduce the number of dimensions.
The following question bugs me - will PCA keep the order of the points in my series so that I can reuse the index from the original dataframe?
df = pd.DataFrame(...)... | https://stackoverflow.com/questions/41981441/keep-pandas-index-while-applying-sklearn | pandas, scikit-learn | 1,485,957,011 |
se_68917363 | stackoverflow | MACHINE_LEARNING | How to resolve: TypeError: fit() missing 1 required positional argument: 'y' | How to resolve: TypeError: fit() missing 1 required positional argument: 'y'
# Decision Tree
from sklearn.tree import DecisionTreeClassifier
clf = DecisionTreeClassifier()
clf = DecisionTreeClassifier.fit(X_train, y_train)
y_pred = DecisionTreeClassifier.predict(X_test)
print(r2_score(y_test, y_pred))
pri... | https://stackoverflow.com/questions/68917363/how-to-resolve-typeerror-fit-missing-1-required-positional-argument-y | python, python-3.x, scikit-learn | 1,629,869,919 |
se_79021659 | stackoverflow | MACHINE_LEARNING | Extend LabelEncoder classes | Extend LabelEncoder classes
I have a LabelEncoder with 500 classes.
To store and load it, I used pickle:
with open('../data/label_encoder_v500.pkl', 'rb') as file:
label_encoder = pickle.load(file)
I want to add 24 new classes to this encoder, keeping existing labels unchanged.
additional_classes = ['class501', '... | https://stackoverflow.com/questions/79021659/extend-labelencoder-classes | python, scikit-learn, label-encoding | 1,727,250,397 |
se_79018913 | stackoverflow | MACHINE_LEARNING | ValueError: setting an array element with a sequence. No irregular datatype or jagged array not a duplicate | ValueError: setting an array element with a sequence. No irregular datatype or jagged array not a duplicate
Ok, I found this weird.
I am building a text classifier. I have used the gensim's word2vec with aggregation when I try to run it through an sklearn classifier it gives me the ValueError: setting an array element... | https://stackoverflow.com/questions/79018913/valueerror-setting-an-array-element-with-a-sequence-no-irregular-datatype-or-j | python, numpy, scikit-learn | 1,727,185,738 |
se_36652196 | stackoverflow | MACHINE_LEARNING | How to make FeatureUnion return Dataframe | How to make FeatureUnion return Dataframe
So I currently have a Pipeline that has a lot of customer transformers:
p = Pipeline([
("GetTimeFromDate",TimeTransformer("Date")), #Custom Transformer that adds ["time"] column
("GetZipFromAddress",ZipTransformer("Address")), #Custom Transformer that adds ["zip"] column
("Gr... | https://stackoverflow.com/questions/36652196/how-to-make-featureunion-return-dataframe | python-2.7, machine-learning, scikit-learn, pipeline, feature-extraction | 1,460,737,094 |
se_52269187 | stackoverflow | MACHINE_LEARNING | Facing ValueError: Target is multiclass but average='binary' | Facing ValueError: Target is multiclass but average='binary'
I'm trying to use Naive Bayes algorithm for my dataset. I'm able to find out the accuracy but trying to find out precision and recall for the same. But, it is throwing the following error:
ValueError: Target is multiclass but average='binary'. Please... | https://stackoverflow.com/questions/52269187/facing-valueerror-target-is-multiclass-but-average-binary | python, machine-learning, scikit-learn, valueerror, precision-recall | 1,536,643,684 |
se_62759662 | stackoverflow | MACHINE_LEARNING | Is there a way to convert a single LightGBM decision tree (decision rules) to Python code (conditional statements)? | Is there a way to convert a single LightGBM decision tree (decision rules) to Python code (conditional statements)?
I am trying to convert a single LightGBM decision tree i.e.
num_boost_round = 1
with
num_leaves = 16
to Python conditional statements. Is there a way to do this? I found a post on stackoverflow about ... | https://stackoverflow.com/questions/62759662/is-there-a-way-to-convert-a-single-lightgbm-decision-tree-decision-rules-to-py | python, scikit-learn, decision-tree, lightgbm | 1,594,050,426 |
se_10526579 | stackoverflow | MACHINE_LEARNING | Use scikit-learn to classify into multiple categories | Use scikit-learn to classify into multiple categories
I'm trying to use one of scikit-learn's supervised learning methods to classify pieces of text into one or more categories. The predict function of all the algorithms I tried just returns one match.
For example I have a piece of text:
"Theaters in New York compar... | https://stackoverflow.com/questions/10526579/use-scikit-learn-to-classify-into-multiple-categories | python, classification, scikit-learn | 1,336,615,171 |
se_73226353 | stackoverflow | MACHINE_LEARNING | Clip output from sklearn pipeline predict | Clip output from sklearn pipeline predict
Let's see the following pipeline:
scaler = ScalerFactory.get_scaler(scaler_type)
model = MultiOutputRegressor(lgb.LGBMRegressor(metric='tweedie', **hyperparameters))
steps = [('scaler', scaler), ('model', model)]
pipeline = Pipeline(steps)
pipeline.fit(X, y, model__feature_nam... | https://stackoverflow.com/questions/73226353/clip-output-from-sklearn-pipeline-predict | python, python-3.x, scikit-learn, pipeline, scikit-learn-pipeline | 1,659,552,368 |
se_76635503 | stackoverflow | MACHINE_LEARNING | ValueError: multilabel-indicator is not supported confusion matrix | ValueError: multilabel-indicator is not supported confusion matrix
multilabel-indicator is not supported is the error message I get, when trying to run:
can you give me any solution or hint.
import seaborn as sns
sns.heatmap(confusion_matrix(y_test, y_pred), annot = True)
ValueError Tra... | https://stackoverflow.com/questions/76635503/valueerror-multilabel-indicator-is-not-supported-confusion-matrix | python, machine-learning, scikit-learn, classification, confusion-matrix | 1,688,720,761 |
se_30502284 | stackoverflow | MACHINE_LEARNING | A sparse matrix was passed, but dense data is required. Use X.toarray() to convert to a dense numpy array | A sparse matrix was passed, but dense data is required. Use X.toarray() to convert to a dense numpy array
Code goes as follows, I am trying to use training data for GBRT regression trees, same data works good for other classifiers but gives above error for GBRT. please help :
dataset = load_files('train')
vectorizer ... | https://stackoverflow.com/questions/30502284/a-sparse-matrix-was-passed-but-dense-data-is-required-use-x-toarray-to-conve | python, scikit-learn | 1,432,804,738 |
se_54597212 | stackoverflow | MACHINE_LEARNING | Using hyphen/dash in python repository name and package name | Using hyphen/dash in python repository name and package name
I am trying to make my git repository pip-installable. In preparation for that I am restructuring the repo to follow the right conventions. My understanding from looking at other repositories is that I should put all my source code in a package that has the ... | https://stackoverflow.com/questions/54597212/using-hyphen-dash-in-python-repository-name-and-package-name | python, scikit-learn, pip, package, pypi | 1,549,645,639 |
se_65655002 | stackoverflow | MACHINE_LEARNING | cubic spline regression with sklearn? | cubic spline regression with sklearn?
I want to regress very accurately a target which depends non-linearly from a single variable x. In my sklearn pipeline, I use:
pipe = Pipeline([('poly', PolynomialFeatures(3, include_bias=False)), \
('regr', ElasticNet(random_state=0))])
This appears to give ... | https://stackoverflow.com/questions/65655002/cubic-spline-regression-with-sklearn | python, scikit-learn, cubic-spline | 1,610,292,914 |
se_72101295 | stackoverflow | MACHINE_LEARNING | Python : GridSearchCV taking too long to finish running | Python : GridSearchCV taking too long to finish running
I'm attempting to do a grid search to optimize my model but it's taking far too long to execute. My total dataset is only about 15,000 observations with about 30-40 variables. I was successfully able to run a random forest through the gridsearch which took about ... | https://stackoverflow.com/questions/72101295/python-gridsearchcv-taking-too-long-to-finish-running | python, machine-learning, scikit-learn, data-science, cross-validation | 1,651,589,480 |
se_79000471 | stackoverflow | MACHINE_LEARNING | Object of type CustomScaler is not registered/supported with gurobi_ml | Object of type CustomScaler is not registered/supported with gurobi_ml
I have built a CustomScaler to scale my data in sklearn.pipeline.make_pipeline. It contained transform and inversetransform function. When I used gurobipy to optimise the regression model, I got the title error. It is not categorically mentioned on... | https://stackoverflow.com/questions/79000471/object-of-type-customscaler-is-not-registered-supported-with-gurobi-ml | machine-learning, scikit-learn, mathematical-optimization, gurobi | 1,726,703,416 |
se_58020899 | stackoverflow | MACHINE_LEARNING | Fitting KDE with scikitlearn and pandas leads to distributions outside the range of data | Fitting KDE with scikitlearn and pandas leads to distributions outside the range of data
I am fitting a distribution of scores ranging from 1-13 for a set of data using scikit-learn KDE functions and Pandas plot.kde.
I have set the bandwidth with a gridsearchCV method. However, when the distributions are plotted the r... | https://stackoverflow.com/questions/58020899/fitting-kde-with-scikitlearn-and-pandas-leads-to-distributions-outside-the-range | pandas, python-2.7, scikit-learn, probability | 1,568,945,463 |
se_76593906 | stackoverflow | MACHINE_LEARNING | How to resolve "cannot import name '_MissingValues' from 'sklearn.utils._param_validation'" issue when trying to import imblearn? | How to resolve "cannot import name '_MissingValues' from 'sklearn.utils._param_validation'" issue when trying to import imblearn?
I am trying to import imblearn into my python notebook after installing the required modules. However, I am getting the following error:
Additional info: I am usi... | https://stackoverflow.com/questions/76593906/how-to-resolve-cannot-import-name-missingvalues-from-sklearn-utils-param-v | python, python-3.x, scikit-learn, imblearn | 1,688,201,535 |
se_39525716 | stackoverflow | MACHINE_LEARNING | DecisionTreeRegressor 'tree_' attribute documentation (Tree class) | DecisionTreeRegressor 'tree_' attribute documentation (Tree class)
I am trying to find the documentation on the 'Tree' class which is the class of the 'tree_' parameter of a 'DecisionTreeRegressor' but no success.
Would anybody know if this class is documented anywhere please ?
Thanks,
Yoann | https://stackoverflow.com/questions/39525716/decisiontreeregressor-tree-attribute-documentation-tree-class | python, scikit-learn | 1,474,009,998 |
se_74599395 | stackoverflow | MACHINE_LEARNING | How to run Scikit's gp_minimize in parallel? | How to run Scikit's gp_minimize in parallel?
I am unable to make skopt.gp_minimize run at multiple cores. According to the documentation, the parameter n_jobs should set the number of cores. However, setting n_cores>1 seems to have no effect. Here is a minimal example that reproduces the problem:
from skopt import... | https://stackoverflow.com/questions/74599395/how-to-run-scikits-gp-minimize-in-parallel | python, optimization, scikit-learn, anaconda, scikit-optimize | 1,669,632,192 |
se_78989293 | stackoverflow | MACHINE_LEARNING | InconsistentVersionWarning: Trying to unpickle estimator StandardScaler from version 1.2.2 when using version 1.3.2 | InconsistentVersionWarning: Trying to unpickle estimator StandardScaler from version 1.2.2 when using version 1.3.2
I am trying to train a machine learning model which uses the PowerTransformer from scikit-learn to transform my training data. And here is my code:
from sklearn import preprocessing
from sklearn.preproce... | https://stackoverflow.com/questions/78989293/inconsistentversionwarning-trying-to-unpickle-estimator-standardscaler-from-ver | python, scikit-learn | 1,726,473,637 |
se_78891598 | stackoverflow | MACHINE_LEARNING | Persistent Issue Importing KerasClassifier | Persistent Issue Importing KerasClassifier
I’ve been facing a persistent issue with importing the KerasClassifier library in my Python environment, and I’m hoping to get some advice on how to resolve it.
I keep encountering an intermittent issue where the import sometimes works fine, and at other times, I get the foll... | https://stackoverflow.com/questions/78891598/persistent-issue-importing-kerasclassifier | tensorflow, keras, scikit-learn, tensorflow2.0, scikeras | 1,724,145,773 |
se_68442936 | stackoverflow | MACHINE_LEARNING | I'm doing a machine learning project using MNIST data set with jupyter notebook | I'm doing a machine learning project using MNIST data set with jupyter notebook
I'm very new to Machine Learning and I'm writing the python code for performing handwriting recognition on the MNIST dataset in a Jupyter notebook. But when I try to run the notebook I get the following error. Can anyone help me in fig... | https://stackoverflow.com/questions/68442936/im-doing-a-machine-learning-project-using-mnist-data-set-with-jupyter-notebook | python, numpy, machine-learning, scikit-learn | 1,626,707,698 |
se_78984046 | stackoverflow | MACHINE_LEARNING | PartialDependenceDisplay.from_estimator plots having lines with 0 values | PartialDependenceDisplay.from_estimator plots having lines with 0 values
Need to evaluate the two way interaction between two variables after regressor model.
Used PartialDependenceDisplay.from_estimator to plot but the contour lines inside the plot all have value 0.Not sure what might cause this.
Checked the data an... | https://stackoverflow.com/questions/78984046/partialdependencedisplay-from-estimator-plots-having-lines-with-0-values | python, matplotlib, scikit-learn | 1,726,274,050 |
se_78130876 | stackoverflow | MACHINE_LEARNING | ValueError with Scikit-Learn | ValueError with Scikit-Learn
link to car data.csv
My code:
import pandas as pd
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import train_test_split
car_data = pd.read_csv('car_data.csv')
# Create X
X = car_data.drop('Buy Rate', axis=1)
# Create Y
y = car_data['Buy Rate']
clf = Ra... | https://stackoverflow.com/questions/78130876/valueerror-with-scikit-learn | python, pandas, scikit-learn, model | 1,709,944,936 |
se_78981288 | stackoverflow | MACHINE_LEARNING | ClassifierChain with Random Forest: Why is np.nan not supported even though Base Estimator handles it? | ClassifierChain with Random Forest: Why is np.nan not supported even though Base Estimator handles it?
I'm working on a multilabel classification problem using the ClassifierChain approach with RandomForestClassifier as the base estimator. I've encountered an issue where my input matrix X contains np.nan values. When ... | https://stackoverflow.com/questions/78981288/classifierchain-with-random-forest-why-is-np-nan-not-supported-even-though-base | python-3.x, machine-learning, scikit-learn, nan, random-forest | 1,726,215,924 |
se_40142835 | stackoverflow | MACHINE_LEARNING | Image not segmenting properly using DBSCAN | Image not segmenting properly using DBSCAN
I am trying to use DBSCAN from scikitlearn to segment an image based on color. The results I'm getting are . As you can see there are 3 clusters. My goal is to separate the buoys in the picture into different clusters. But obviously they are showing up as the same cluster. ... | https://stackoverflow.com/questions/40142835/image-not-segmenting-properly-using-dbscan | opencv, scikit-learn, computer-vision, image-segmentation, dbscan | 1,476,917,875 |
se_69469083 | stackoverflow | MACHINE_LEARNING | Machine learning not predicting correct results | Machine learning not predicting correct results
I am working on creating a simple Python machine learning script which will predict if loan will be approved or not based on below parameters
business experience: should be greater than 7
year of founded: should be after 2015
loan: no previous or current loan
If above c... | https://stackoverflow.com/questions/69469083/machine-learning-not-predicting-correct-results | python, machine-learning, scikit-learn, logistic-regression | 1,633,536,440 |
se_60043276 | stackoverflow | MACHINE_LEARNING | ValueError: With n_samples=0, test_size=0.2 and train_size=None, the resulting train set will be empty. Adjust any of the aforementioned parameters | ValueError: With n_samples=0, test_size=0.2 and train_size=None, the resulting train set will be empty. Adjust any of the aforementioned parameters
I wrote a text classification program. When I run the program it crashes with an error as seen in this screenshot:
ValueError: With n_samples=0, test_size=0.2 and train_... | https://stackoverflow.com/questions/60043276/valueerror-with-n-samples-0-test-size-0-2-and-train-size-none-the-resulting-t | python, scikit-learn, nlp | 1,580,747,106 |
se_66094139 | stackoverflow | MACHINE_LEARNING | Issue setting up SciKeras model | Issue setting up SciKeras model
I have an existing setup using scikit-learn, but am looking into expanding into deep learning with Keras. I am also using Dask, which recommends using SciKeras.
The way the SciKeras KerasClassifier is currently setup, seems to fit as expected (from the verbose output), but the model see... | https://stackoverflow.com/questions/66094139/issue-setting-up-scikeras-model | python, machine-learning, keras, scikit-learn, deep-learning | 1,612,739,996 |
se_72583838 | stackoverflow | MACHINE_LEARNING | ModuleNotFoundError: No module named 'numpy.random.bit_generator' while importing sklearn | ModuleNotFoundError: No module named 'numpy.random.bit_generator' while importing sklearn
I installed opencv, tensorflow and other tools on my Macbook M1 air by watching this tutorial:
After installing, opencv and tensorflow works fine but when I try to import sklearn the mentioned error occurs. Here is the Er... | https://stackoverflow.com/questions/72583838/modulenotfounderror-no-module-named-numpy-random-bit-generator-while-importin | numpy, opencv, scikit-learn, conda, mini-forge | 1,654,945,982 |
se_78958361 | stackoverflow | MACHINE_LEARNING | Is it possible to transform a target variable using `ravel()` or `to_numpy()` in a `sklearn` pipeline? | Is it possible to transform a target variable using `ravel()` or `to_numpy()` in a `sklearn` pipeline?
I am using RStudio and tidymodels in an R markdown document. I would like to incorporate some models from scikit-learn. Getting data from the R code chunks to the Python code chunk works well, but when I train and te... | https://stackoverflow.com/questions/78958361/is-it-possible-to-transform-a-target-variable-using-ravel-or-to-numpy-in | python, r, machine-learning, scikit-learn | 1,725,647,505 |
se_38733220 | stackoverflow | MACHINE_LEARNING | Difference between scikit-learn and sklearn (now deprecated) | Difference between scikit-learn and sklearn (now deprecated)
On OS X 10.11.6 and python 2.7.10 I need to import from sklearn manifold.
I have numpy 1.8 Orc1, scipy .13 Ob1 and scikit-learn 0.17.1 installed.
I used pip to install sklearn(0.0), but when I try to import from sklearn manifold I get the following:
T... | https://stackoverflow.com/questions/38733220/difference-between-scikit-learn-and-sklearn-now-deprecated | python, python-3.x, python-2.7, scikit-learn | 1,470,190,041 |
se_71550664 | stackoverflow | MACHINE_LEARNING | Library data extraction from a python syntax using AST(Abstract Syntax Tree) module | Library data extraction from a python syntax using AST(Abstract Syntax Tree) module
"""
import sklearn as sk
from sklearn.ensemble import ExtraTreesRegressor
from sklearn.model_selection import train_test_split
selection = ExtraTreesRegressor()
selection.fit(X,y)
X_train, X_test, y_train, y_test = train_test_split(X, ... | https://stackoverflow.com/questions/71550664/library-data-extraction-from-a-python-syntax-using-astabstract-syntax-tree-mod | python, json, scikit-learn, extract, abstract-syntax-tree | 1,647,810,526 |
se_50957340 | stackoverflow | MACHINE_LEARNING | Isolation Forest Sklearn for 1D array or list and how to tune hyper parameters | Isolation Forest Sklearn for 1D array or list and how to tune hyper parameters
Is there a way to implement sklearn isolation forest for a 1D array or list? All the examples I came across are for data of 2 Dimension or more.
I have right now developed a model with three features and the example code snipped is mentione... | https://stackoverflow.com/questions/50957340/isolation-forest-sklearn-for-1d-array-or-list-and-how-to-tune-hyper-parameters | python, algorithm, machine-learning, scikit-learn, anomaly-detection | 1,529,530,337 |
se_78963115 | stackoverflow | MACHINE_LEARNING | Can I force sklearn to use float32 instead of float64? | Can I force sklearn to use float32 instead of float64?
I am building a product recommender that will use the description of products to find similar products and recommend them. I am using CountVectorizer over the description to find semantically similar descriptions, rank them and suggest those similar.
The problem c... | https://stackoverflow.com/questions/78963115/can-i-force-sklearn-to-use-float32-instead-of-float64 | python, scikit-learn, ram, cosine-similarity | 1,725,822,022 |
se_78969301 | stackoverflow | MACHINE_LEARNING | Loading a pipeline with a dense-array conversion step | Loading a pipeline with a dense-array conversion step
I trained and saved the following model using joblib:
def to_dense(x):
return np.asarray(x.todense())
to_dense_array = FunctionTransformer(to_dense, accept_sparse=True)
model = make_pipeline(
TfidfVectorizer(),
to_dense_array,
HistGradientBoosting... | https://stackoverflow.com/questions/78969301/loading-a-pipeline-with-a-dense-array-conversion-step | python, numpy, scikit-learn, numpy-ndarray, joblib | 1,725,968,212 |
se_78963884 | stackoverflow | MACHINE_LEARNING | Simulating scikit-learn's OneHotEncoder mixed data type error | Simulating scikit-learn's OneHotEncoder mixed data type error
My focus is on the caveat mentioned in OneHotEncoder's list parameter doc.
list : categories[i] holds the categories expected in the ith column.
The passed categories should not mix strings and numeric values within
a single feature, and should be sort... | https://stackoverflow.com/questions/78963884/simulating-scikit-learns-onehotencoder-mixed-data-type-error | python-3.x, pandas, dataframe, scikit-learn | 1,725,856,225 |
se_40845304 | stackoverflow | MACHINE_LEARNING | RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility | RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility
I have this error for trying to load a saved SVM model. I have tried uninstalling sklearn, NumPy and SciPy, reinstalling the latest versions all-together again (using pip). I am still getting this error. Why?
In [1]: import sklearn; print s... | https://stackoverflow.com/questions/40845304/runtimewarning-numpy-dtype-size-changed-may-indicate-binary-incompatibility | python, numpy, scikit-learn | 1,480,339,068 |
se_78949366 | stackoverflow | MACHINE_LEARNING | Is there a way to use SciPy's differential evolution, or another library, to minimize one of a multi-output regressor's outs and bound the others? | Is there a way to use SciPy's differential evolution, or another library, to minimize one of a multi-output regressor's outs and bound the others?
I am using a simple RandomForestRegressor from sklearn to predict 3 outputs, and it works well. The problem is that I now need to optimize one of the outputs to be ... | https://stackoverflow.com/questions/78949366/is-there-a-way-to-use-scipys-differential-evolution-or-another-library-to-min | python, scikit-learn, scipy, mathematical-optimization, differential-evolution | 1,725,462,832 |
se_41666627 | stackoverflow | MACHINE_LEARNING | Using own image in sklearn digits example | Using own image in sklearn digits example
So I've been toying around with sklearn and python and try to understand how machine learning works. I got the basic examples right but there's one thing I'm struggling with.
For example let's say I'm using the digits dataset, once I got my classifier ready and tested. How wo... | https://stackoverflow.com/questions/41666627/using-own-image-in-sklearn-digits-example | python, machine-learning, scikit-learn | 1,484,516,368 |
se_78948520 | stackoverflow | MACHINE_LEARNING | Using StratifiedGroupKFold in StackingClassifier | Using StratifiedGroupKFold in StackingClassifier
How to specify StratifiedGroupKFold within StackingClassifier in sklearn?
from sklearn.datasets import load_iris
from sklearn.ensemble import RandomForestClassifier
from sklearn.svm import NuSVC
from sklearn.linear_model import LogisticRegression
from sklearn.preprocess... | https://stackoverflow.com/questions/78948520/using-stratifiedgroupkfold-in-stackingclassifier | python, scikit-learn | 1,725,451,098 |
se_78953273 | stackoverflow | MACHINE_LEARNING | Importing a Model with Scikit Learn on Vertex | Importing a Model with Scikit Learn on Vertex
I'm trying to import a model from my local but everytime I get the same error from gcp logs. The framework is scikit-learn
AttributeError: Can't get attribute 'preprocess_text' on <module 'model_server' from '/usr/app/model_server.py'>
The code snippet with this problem i... | https://stackoverflow.com/questions/78953273/importing-a-model-with-scikit-learn-on-vertex | machine-learning, google-cloud-platform, scikit-learn, google-cloud-vertex-ai | 1,725,542,674 |
se_72464571 | stackoverflow | MACHINE_LEARNING | precision_recall_fscore_support support returns None | precision_recall_fscore_support support returns None
I'm trying to extract all the relevant 'weighted average' measures from classification report.
I get the recall, precision and fscore correct. support, however returns None, whereas I expect it to be, 500 which is the total of 'yes' in my multiclass classification.
... | https://stackoverflow.com/questions/72464571/precision-recall-fscore-support-support-returns-none | scikit-learn, classification | 1,654,097,743 |
se_48758383 | stackoverflow | MACHINE_LEARNING | All intermediate steps should be transformers and implement fit and transform | All intermediate steps should be transformers and implement fit and transform
I am implementing a pipeline using important features selection and then using the same features to train my random forest classifier. Following is my code.
m = ExtraTreesClassifier(n_estimators = 10)
m.fit(train_cv_x,train_cv_y)
sel = Selec... | https://stackoverflow.com/questions/48758383/all-intermediate-steps-should-be-transformers-and-implement-fit-and-transform | python, machine-learning, scikit-learn, typeerror, feature-selection | 1,518,487,189 |
se_68869466 | stackoverflow | MACHINE_LEARNING | Use sklearn transformers on list of columns and preserve the input columns | Use sklearn transformers on list of columns and preserve the input columns
Using sklearn transformers, I'd like to be able to apply transformations to a list of columns and have the transformer create new columns with the transformed values rather than apply them to the existing ones. Is this possible? The transformer... | https://stackoverflow.com/questions/68869466/use-sklearn-transformers-on-list-of-columns-and-preserve-the-input-columns | python, scikit-learn | 1,629,509,314 |
se_78203591 | stackoverflow | MACHINE_LEARNING | Problem with the installation of scikit multiflow | Problem with the installation of scikit multiflow
When I try to install scikit-multiflow library into a virtual environment using pip in command prompt, I constantly get this issue because there is no file called 'numpy.distutils', despite installing numpy library and Microsoft Vedio Studio Installer with version 14.0... | https://stackoverflow.com/questions/78203591/problem-with-the-installation-of-scikit-multiflow | scikit-learn, scikit-multilearn | 1,711,071,077 |
se_78940566 | stackoverflow | MACHINE_LEARNING | How do I convert string data to numerical data using Label Encoder? | How do I convert string data to numerical data using Label Encoder?
I was trying to convert string data into numerical data in a CSV excel sheet. It kept giving me an error about previously unseen labels, so I searched it up and found that we can use Label Encoder to convert all these values to numeric. I created a li... | https://stackoverflow.com/questions/78940566/how-do-i-convert-string-data-to-numerical-data-using-label-encoder | python, pandas, scikit-learn, label-encoding | 1,725,281,638 |
se_78938692 | stackoverflow | MACHINE_LEARNING | Reconciling disparity between test-accuracy and confusion matrix in tensorflow | Reconciling disparity between test-accuracy and confusion matrix in tensorflow
Update: it's definitely something going on with the the predict function using a custom generator. When I fetch all the test data in one batch and run predictions on it, then create a confusion matrix between predictions and labels, I get w... | https://stackoverflow.com/questions/78938692/reconciling-disparity-between-test-accuracy-and-confusion-matrix-in-tensorflow | python, tensorflow, scikit-learn | 1,725,241,616 |
se_78928473 | stackoverflow | MACHINE_LEARNING | What does `fit_transform` do in the context of Scikit Learn PCA? | What does `fit_transform` do in the context of Scikit Learn PCA?
I don't understand what fit_transform does compared to fit in the context of Scikit Learn and PCA.
https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html#
PCA takes some data and attempts to measure a set of eigenvectors, wher... | https://stackoverflow.com/questions/78928473/what-does-fit-transform-do-in-the-context-of-scikit-learn-pca | scikit-learn, pca | 1,724,943,696 |
se_78935707 | stackoverflow | MACHINE_LEARNING | Apply Scaler() on each ID on polars dataframe | Apply Scaler() on each ID on polars dataframe
I have a dataset with multiple columns and an ID column. Each ID can have different magnitudes and varying sizes across these columns. I want to normalize the columns for each ID separately.
import polars as pl
from sklearn.preprocessing import MinMaxScaler
scaler = MinMa... | https://stackoverflow.com/questions/78935707/apply-scaler-on-each-id-on-polars-dataframe | python, scikit-learn, python-polars | 1,725,124,178 |
se_72648690 | stackoverflow | MACHINE_LEARNING | ML model error 'numpy.ndarray' object has no attribute 'predict' | ML model error 'numpy.ndarray' object has no attribute 'predict'
I was trying to make a predictive model, but I can't find a way to solve this numpy-related issue with my code. I already imported the pickle file containing the model I saved from Google Colab, but I can't seem to make it work. Any type ... | https://stackoverflow.com/questions/72648690/ml-model-error-numpy-ndarray-object-has-no-attribute-predict | python, pandas, numpy, flask, scikit-learn | 1,655,395,059 |
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