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_79259003 | stackoverflow | MACHINE_LEARNING | Why do scikit-learn predict(X) methods accept a 2D matrix rather than a 1D vector? | Why do scikit-learn predict(X) methods accept a 2D matrix rather than a 1D vector?
Does anyone know why the predict(X) methods of scikit-learn classifiers and regressors expect input X to be a 2D array (matrix) rather than a 1D array (vector)? I'm just curious about the history of the design.
With the existing design,... | https://stackoverflow.com/questions/79259003/why-do-scikit-learn-predictx-methods-accept-a-2d-matrix-rather-than-a-1d-vecto | methods, scikit-learn, predict | 1,733,509,775 |
se_79242610 | stackoverflow | MACHINE_LEARNING | Implementing sklearn.ensemble.GradientBoostingRegressor with sklearn.multioutput.MultiOutputRegressor and sklearn.model_selection.RandomizedSearchCV | Implementing sklearn.ensemble.GradientBoostingRegressor with sklearn.multioutput.MultiOutputRegressor and sklearn.model_selection.RandomizedSearchCV
I'm trying to create models that support multivariate output. One of the models I'm trying to use is the GradientBoostingRegressor which does not natively support multiva... | https://stackoverflow.com/questions/79242610/implementing-sklearn-ensemble-gradientboostingregressor-with-sklearn-multioutput | python, scikit-learn | 1,733,093,388 |
se_65048479 | stackoverflow | MACHINE_LEARNING | Unable to run autosklearn on colab | Unable to run autosklearn on colab
I am trying to run auto-sklearn on Google colab. I have successfully installed AutoSklearn but it gives me error while running following code:
Input:
import autosklearn.classfication
Output:
---------------------------------------------------------------------------
IncorrectPac... | https://stackoverflow.com/questions/65048479/unable-to-run-autosklearn-on-colab | scikit-learn, google-colaboratory | 1,606,558,408 |
se_70278059 | stackoverflow | MACHINE_LEARNING | Plotting the ROC curve for a multiclass problem | Plotting the ROC curve for a multiclass problem
I am trying to apply the idea of sklearn ROC extension to multiclass to my dataset. My per-class ROC curve looks find of a straight line each, unline the sklearn's example showing curve's fluctuating.
I give an MWE below to show what I mean:
# all imports
import numpy as... | https://stackoverflow.com/questions/70278059/plotting-the-roc-curve-for-a-multiclass-problem | python, machine-learning, scikit-learn, roc, auc | 1,638,979,334 |
se_79249247 | stackoverflow | MACHINE_LEARNING | How do I make a neural network class with fit and predict functions like with sklearn models, when my train and test data are different sizes? | How do I make a neural network class with fit and predict functions like with sklearn models, when my train and test data are different sizes?
I'm trying to make a neural network model that will answer a linear regression problem (I've already made a model using sklearn's LinearRegression and I'd like to compare the t... | https://stackoverflow.com/questions/79249247/how-do-i-make-a-neural-network-class-with-fit-and-predict-functions-like-with-sk | machine-learning, scikit-learn, pytorch, neural-network, linear-regression | 1,733,262,070 |
se_71181291 | stackoverflow | MACHINE_LEARNING | What is the difference between RepeatedStratifiedKFold and StratifiedKFold in sklearn? | What is the difference between RepeatedStratifiedKFold and StratifiedKFold in sklearn?
I tried to read the docs for RepeatedStratifiedKFold and StratifiedKFold, but couldn't tell the difference between the two methods, except that RepeatedStratifiedKFold repeats StratifiedKFold n times with different randomization in... | https://stackoverflow.com/questions/71181291/what-is-the-difference-between-repeatedstratifiedkfold-and-stratifiedkfold-in-sk | python, machine-learning, scikit-learn, classification, cross-validation | 1,645,230,161 |
se_70557002 | stackoverflow | MACHINE_LEARNING | Why does sklearn tf-idf vectorizer give the highest scores to stopwords? | Why does sklearn tf-idf vectorizer give the highest scores to stopwords?
I implemented Tf-idf with sklearn for each category of the Brown corpus in nltk library. There are 15 categories and for each of them the highest score is assigned to a stopword.
The default parameter is use_idf=True, so I'm using idf. The corpus... | https://stackoverflow.com/questions/70557002/why-does-sklearn-tf-idf-vectorizer-give-the-highest-scores-to-stopwords | python, scikit-learn, nltk, tf-idf, tfidfvectorizer | 1,641,135,423 |
se_70727739 | stackoverflow | MACHINE_LEARNING | TfidfVectorizer seems to be giving incorrect results | TfidfVectorizer seems to be giving incorrect results
I have a list of length 7 (7 subjectes)
Each element in the list contains a long string of words.
Each element of the list can be viewed as a topic with a long sentence that sets it apart
I want to check which words make each topic unique (each element in the list)
... | https://stackoverflow.com/questions/70727739/tfidfvectorizer-seems-to-be-giving-incorrect-results | python, scikit-learn, nlp, tf-idf, tfidfvectorizer | 1,642,312,988 |
se_66249963 | stackoverflow | MACHINE_LEARNING | sklearn mutual_info_classif returns different values depending on feature order | sklearn mutual_info_classif returns different values depending on feature order
I noticed behavior in the sklearn mutual_info_classif function that is inconsistent with what I expect in the mutual information objective.
Given a set of columns ['A', 'B', 'C'] and a dependent variable y, the mutual information computed... | https://stackoverflow.com/questions/66249963/sklearn-mutual-info-classif-returns-different-values-depending-on-feature-order | python, scikit-learn, entropy | 1,613,596,058 |
se_79244221 | stackoverflow | MACHINE_LEARNING | Feature Importance with ColumnTransform and OneHotEncoder in RandomForestClassifier | Feature Importance with ColumnTransform and OneHotEncoder in RandomForestClassifier
Apologies for bothering you, but I haven't been able to find a definitive answer after searching the site.
I'm building a RandomForestClassifier on some clinical data where the target variable (outcome) is binary (0 or 1). I'm using Py... | https://stackoverflow.com/questions/79244221/feature-importance-with-columntransform-and-onehotencoder-in-randomforestclassif | python, scikit-learn, pipeline, random-forest | 1,733,144,944 |
se_59287936 | stackoverflow | MACHINE_LEARNING | Custom estimator for sklearn with a lot of params | Custom estimator for sklearn with a lot of params
I am trying to make custom estimator for sklearn with a lot of params. As i understand, i should do something like this:
class MyEstim(BaseEstimator):
def __init__(self, param1, param2):
super().__init__()
self.param1 = param1
self.param2 = ... | https://stackoverflow.com/questions/59287936/custom-estimator-for-sklearn-with-a-lot-of-params | python, parameters, scikit-learn | 1,576,074,298 |
se_44443479 | stackoverflow | MACHINE_LEARNING | How to show loss values during training in scikit-learn? | How to show loss values during training in scikit-learn?
I want check my loss values during the training time so I can observe the loss at each iteration. So far I haven't found an easy way for scikit learn to give me a history of loss values, nor did I find a functionality already within scikit to plot the loss for m... | https://stackoverflow.com/questions/44443479/how-to-show-loss-values-during-training-in-scikit-learn | python, machine-learning, scikit-learn | 1,496,947,855 |
se_79232519 | stackoverflow | MACHINE_LEARNING | Is the GaussianProcessRegressor estimator in scikit-learn able to be parallelized on multi-core? | Is the GaussianProcessRegressor estimator in scikit-learn able to be parallelized on multi-core?
I do not notice any performance improvements when using GaussianProcessRegressor on a machine which has 8 cores (16 threads), although i do only use physical cores. So I wonder, is the GaussianProcessRegressor class in skl... | https://stackoverflow.com/questions/79232519/is-the-gaussianprocessregressor-estimator-in-scikit-learn-able-to-be-parallelize | machine-learning, scikit-learn, python-multiprocessing, gaussian-process | 1,732,765,016 |
se_79237483 | stackoverflow | MACHINE_LEARNING | Discrepancy between sklearn's r2_score() and PyTorch's MSELoss()? | Discrepancy between sklearn's r2_score() and PyTorch's MSELoss()?
I am not sure if I am missing something very basic but I have started to notice some slight discrepancies between R2 scores returned by sklearn's r2_score() function and R2 scores calculated from PyTorch's MSELoss() (with the additional help of ... | https://stackoverflow.com/questions/79237483/discrepancy-between-sklearns-r2-score-and-pytorchs-mseloss | scikit-learn, pytorch | 1,732,891,551 |
se_55632010 | stackoverflow | MACHINE_LEARNING | Using scikit-learn's MLPClassifier in AdaBoostClassifier | Using scikit-learn's MLPClassifier in AdaBoostClassifier
For a binary classification problem I want to use the MLPClassifier as the base estimator in the AdaBoostClassifier. However, this does not work because MLPClassifier does not implement sample_weight, which is required for AdaBoostClassifier (see here). Befo... | https://stackoverflow.com/questions/55632010/using-scikit-learns-mlpclassifier-in-adaboostclassifier | machine-learning, scikit-learn, neural-network, adaboost | 1,554,984,049 |
se_68586561 | stackoverflow | MACHINE_LEARNING | sklearn: multi-class problem and reporting sensitivity and specificity | sklearn: multi-class problem and reporting sensitivity and specificity
I have a three-class problem and I'm able to report precision and recall for each class with the below code:
from sklearn.metrics import classification_report
print(classification_report(y_test, y_pred))
which gives me the precision and recall nic... | https://stackoverflow.com/questions/68586561/sklearn-multi-class-problem-and-reporting-sensitivity-and-specificity | python, scikit-learn, classification, supervised-learning | 1,627,627,692 |
se_78699230 | stackoverflow | MACHINE_LEARNING | How to save single Random Forest model with cross validation? | How to save single Random Forest model with cross validation?
I am using 10 fold cross validation, trying to predict binary labels (Y) based on the embedding inputs (X).
I want to save one of the models (perhaps the one with the highest ROC AUC). I'm not sure how to do it because the ROC AUCs are not stored and I don'... | https://stackoverflow.com/questions/78699230/how-to-save-single-random-forest-model-with-cross-validation | python, pandas, numpy, scikit-learn, cross-validation | 1,719,954,145 |
se_69836915 | stackoverflow | MACHINE_LEARNING | Sklearn built-in function for Hard margin SVM | Sklearn built-in function for Hard margin SVM
I know that there is a built-in function for soft margin SVM as follows.
from sklearn.svm import SVC
clf = SVC(C=1, kernel = 'linear')
clf.fit(X, y)
But for Hard margin SVM, we need C=0, right? But the code report error ValueError: C <= 0 when I let C=0. | https://stackoverflow.com/questions/69836915/sklearn-built-in-function-for-hard-margin-svm | python, scikit-learn, svm | 1,636,017,719 |
se_79210867 | stackoverflow | MACHINE_LEARNING | Is there a way to load a saved SKLearn VectorStore using langchain? | Is there a way to load a saved SKLearn VectorStore using langchain?
I created and saved a vectorstore using langchain_community.vectorstores SKLearnVectorStore and I can't load it.
I created and saved vectorstore as below:
from langchain_community.vectorstores import SKLearnVectorStore
vectorstore = SKLearnVectorStor... | https://stackoverflow.com/questions/79210867/is-there-a-way-to-load-a-saved-sklearn-vectorstore-using-langchain | scikit-learn, langchain, rag, vectorstore | 1,732,187,234 |
se_42178070 | stackoverflow | MACHINE_LEARNING | Jupyter Notebook ImportError: No module named 'sklearn' | Jupyter Notebook ImportError: No module named 'sklearn'
I am trying to run on my local machine. I get an error
ImportError: No module named 'sklearn' only in jupyter notebook
It works fine when I use python from the command line both with the carnd-term1 env activated and deactivated.
I have installed sklea... | https://stackoverflow.com/questions/42178070/jupyter-notebook-importerror-no-module-named-sklearn | scikit-learn, jupyter-notebook, conda | 1,486,829,322 |
se_77907033 | stackoverflow | MACHINE_LEARNING | sklearn "transform_output" setting different in Flask application context v request context | sklearn "transform_output" setting different in Flask application context v request context
I'm working on modifying a working Flask application I've been using to serve an ML model to now serve predictions from a new, updated model.
The model is an sklearn pipeline object I've trained and serialized using t... | https://stackoverflow.com/questions/77907033/sklearn-transform-output-setting-different-in-flask-application-context-v-requ | machine-learning, flask, scikit-learn, pipeline, werkzeug | 1,706,624,266 |
se_79208596 | stackoverflow | MACHINE_LEARNING | Custom Scikit-learn Model Persistence | Custom Scikit-learn Model Persistence
I know there are several out of the box methods of saving the model.
However I want to save the model as a database blob.
I've seen examples where people extract 'coefs' etc from the dict of the estimator but when I try this with RandomForrestRegressor (for example) it says there ... | https://stackoverflow.com/questions/79208596/custom-scikit-learn-model-persistence | scikit-learn, persistence | 1,732,128,642 |
se_66956197 | stackoverflow | MACHINE_LEARNING | VS Code: ModuleNotFoundError: No module named 'sklearn' | VS Code: ModuleNotFoundError: No module named 'sklearn'
I am working in VS Code to run a Python script in conda environment named myenv where sklearn is already installed. However when I import it and run the script I get the following error:
Traceback (most recent call last):
File "d:\ML\Project\src\train.... | https://stackoverflow.com/questions/66956197/vs-code-modulenotfounderror-no-module-named-sklearn | python, python-3.x, visual-studio-code, scikit-learn, pip | 1,617,639,778 |
se_66154986 | stackoverflow | MACHINE_LEARNING | Why am I getting 100% accuracy when using a Linear Regression model to predict stock prices? | Why am I getting 100% accuracy when using a Linear Regression model to predict stock prices?
I'm trying to predict stock prices in python using a linear regression model. I split the data using train_test_split so from what I understand, my test data should not be in my training data so I do not understand why the mod... | https://stackoverflow.com/questions/66154986/why-am-i-getting-100-accuracy-when-using-a-linear-regression-model-to-predict-s | python, machine-learning, scikit-learn, linear-regression | 1,613,047,243 |
se_12738827 | stackoverflow | MACHINE_LEARNING | How can I call scikit-learn classifiers from Java? | How can I call scikit-learn classifiers from Java?
I have a classifier that I trained using Python's scikit-learn. How can I use the classifier from a Java program? Can I use Jython? Is there some way to save the classifier in Python and load it in Java? Is there some other way to use it? | https://stackoverflow.com/questions/12738827/how-can-i-call-scikit-learn-classifiers-from-java | java, python, jython, scikit-learn | 1,349,405,426 |
se_61882244 | stackoverflow | MACHINE_LEARNING | Sk-learn GridSearchCV fits on full data | Sk-learn GridSearchCV fits on full data
I used sklearn GridSearchCV to search # of topics using lda model. After fitting the model, the fitted model is saved in CV_model.best_estimator_. Based on sklearn docs, GridSearchCV has default option refit, default=True, which 'Refit an estimator using the best found parameter... | https://stackoverflow.com/questions/61882244/sk-learn-gridsearchcv-fits-on-full-data | machine-learning, scikit-learn, topic-modeling, grid-search | 1,589,855,347 |
se_49408371 | stackoverflow | MACHINE_LEARNING | When to use min-max-scalar and standard-scalar? | When to use min-max-scalar and standard-scalar?
When should I use min-max-scaler and when Standard Scalar?
I think it depends on the data. Are there any features of data to look out for to decide which preprocessing method to go for?
I looked at the docs but can someone give me more insight into it? | https://stackoverflow.com/questions/49408371/when-to-use-min-max-scalar-and-standard-scalar | python-3.x, scikit-learn | 1,521,640,793 |
se_75941142 | stackoverflow | MACHINE_LEARNING | Speedup Sklearn model fitting | Speedup Sklearn model fitting
I am profiling Sklearn model:
clf = GridSearchCV(..., n_jobs=-1)
%time clf.fit(X_train, y_train)
...
CPU times: user 2min 35s, sys: 3.07 s, total: 2min 38s
Wall time: 8min 40s
Wall Time is significantly larger than CPU total time.
Does it mean, that Sklearn is not fully utilizing CP... | https://stackoverflow.com/questions/75941142/speedup-sklearn-model-fitting | python, performance, scikit-learn, jupyter-notebook, thread-priority | 1,680,707,514 |
se_59157093 | stackoverflow | MACHINE_LEARNING | Download sklearn datasets behind a proxy | Download sklearn datasets behind a proxy
I installed sklearn in my enviorment and running it now on jupyter notebook on windows.
How can I avoid the error:
URLError: urlopen error [Errno 11004] getaddrinfo failed
I am running the following code:
import sklearn
import sklearn.ensemble
import sklearn.metrics
fro... | https://stackoverflow.com/questions/59157093/download-sklearn-datasets-behind-a-proxy | python, scikit-learn | 1,575,375,911 |
se_79197656 | stackoverflow | MACHINE_LEARNING | How to reduce the size of Numpy data type | How to reduce the size of Numpy data type
I am using Python to do cosine similarity.
similarity_matrix = cosine_similarity(tfidf_matrix)
The problem is that I am getting this error
MemoryError: Unable to allocate 44.8 GiB for an array with shape (6011226750,) and data type float64
I don't think I need float64 for th... | https://stackoverflow.com/questions/79197656/how-to-reduce-the-size-of-numpy-data-type | python, numpy, scikit-learn, cosine-similarity | 1,731,861,709 |
se_64068419 | stackoverflow | MACHINE_LEARNING | how to visualize the iris dataset on 2d plots for different combinations of features | how to visualize the iris dataset on 2d plots for different combinations of features
I want to visualize the iris dataset in 2d with all six combinations (sepal width-sepal length) , (petal width-sepal length), (sepal length-petal width), (petal length-petal width) (petal length-sepal width) (sepal width-petal length)... | https://stackoverflow.com/questions/64068419/how-to-visualize-the-iris-dataset-on-2d-plots-for-different-combinations-of-feat | python, machine-learning, scikit-learn | 1,601,053,230 |
se_79075564 | stackoverflow | MACHINE_LEARNING | What is the best way to fit a quadratic polynomial to p-dimensional data and compute its gradient and Hessian matrix? | What is the best way to fit a quadratic polynomial to p-dimensional data and compute its gradient and Hessian matrix?
I have been trying to use the scikit-learn library to solve this problem. Roughly:
from sklearn.preprocessing import PolynomialFeatures
from sklearn.linear_model import LinearRegression
# Make or loa... | https://stackoverflow.com/questions/79075564/what-is-the-best-way-to-fit-a-quadratic-polynomial-to-p-dimensional-data-and-com | python, scikit-learn, linear-regression, polynomials, hessian-matrix | 1,728,581,532 |
se_31948879 | stackoverflow | MACHINE_LEARNING | Using explicit (predefined) validation set for grid search with sklearn | Using explicit (predefined) validation set for grid search with sklearn
I have a dataset, which has previously been split into 3 sets: train, validation and test. These sets have to be used as given in order to compare the performance across different algorithms.
I would now like to optimize the parameters of my SVM ... | https://stackoverflow.com/questions/31948879/using-explicit-predefined-validation-set-for-grid-search-with-sklearn | python, validation, scikit-learn, cross-validation | 1,439,316,209 |
se_78554891 | stackoverflow | MACHINE_LEARNING | How to fit a multiple observations to single Gaussian Process | How to fit a multiple observations to single Gaussian Process
I am trying to fit multiple observations to a single Gaussian Process.
I try to fit the data of two observations (Y) like this:
import numpy as np
from sklearn.gaussian_process import GaussianProcessRegressor
from sklearn.gaussian_process.kernels import RBF... | https://stackoverflow.com/questions/78554891/how-to-fit-a-multiple-observations-to-single-gaussian-process | python, machine-learning, scikit-learn, regression, gaussian-process | 1,717,071,370 |
se_71090431 | stackoverflow | MACHINE_LEARNING | Python- How to import DecisionTree Classifier from sklearn.tree | Python- How to import DecisionTree Classifier from sklearn.tree
May I know how to import DecisionTreeClassifier from sklearn.tree as there is an error shown:
ModuleNotFoundError: No module named 'sklearn'
Also, every time when I want to import functions like pandas, I need to pip install them which is time-consuming.... | https://stackoverflow.com/questions/71090431/python-how-to-import-decisiontree-classifier-from-sklearn-tree | python, scikit-learn, decision-tree | 1,644,656,777 |
se_79183884 | stackoverflow | MACHINE_LEARNING | How to use Python to replicate Random Forest Regression prediction using decision paths? | How to use Python to replicate Random Forest Regression prediction using decision paths?
I'm trying to test whether I've understood the way RandomForestRegressor produces forecast after a model's fitted. I used the California housing example to train a simple model and predict the first value in my test set. I then us... | https://stackoverflow.com/questions/79183884/how-to-use-python-to-replicate-random-forest-regression-prediction-using-decisio | machine-learning, scikit-learn, data-science, random-forest | 1,731,484,553 |
se_79182452 | stackoverflow | MACHINE_LEARNING | Ignore NaN to calculate mean_absolute_error | Ignore NaN to calculate mean_absolute_error
I'm trying to calculate MAE (Mean absolute error).
In my original DataFrame, I have 1826 rows and 3 columns. I'm using columns 2 and 3 to calculate MAE.
But, in column 2, I have some NaN values.
When I used:
from sklearn.metrics import mean_absolute_error
and selected these... | https://stackoverflow.com/questions/79182452/ignore-nan-to-calculate-mean-absolute-error | python, pandas, scikit-learn | 1,731,439,210 |
se_79181092 | stackoverflow | MACHINE_LEARNING | Efficient parallelization of silhouette score calculation | Efficient parallelization of silhouette score calculation
I have a large dataset (2 million rows, 100 columns), and I need to perform clusterization. I used the elbow method to determine the optimal number of clusters. However, in order to get a more refined picture, I also need to calculate the silhouette scores for ... | https://stackoverflow.com/questions/79181092/efficient-parallelization-of-silhouette-score-calculation | python, scikit-learn, cluster-analysis, k-means, joblib | 1,731,414,411 |
se_76812504 | stackoverflow | MACHINE_LEARNING | AttributeError: 'RFECV' object has no attribute 'grid_scores_' | AttributeError: 'RFECV' object has no attribute 'grid_scores_'
Problem I faced:
Getting this error continuously AttributeError: 'RFECV' object has no attribute 'grid_scores_'. The code is given below:
from sklearn.ensemble import RandomForestClassifier
from sklearn.feature_selection import RFECV
from s... | https://stackoverflow.com/questions/76812504/attributeerror-rfecv-object-has-no-attribute-grid-scores | python, scikit-learn, attributeerror, feature-selection | 1,690,898,955 |
se_79167713 | stackoverflow | MACHINE_LEARNING | How to create a scaler applying log transformation and MinMaxScaler in sklearn | How to create a scaler applying log transformation and MinMaxScaler in sklearn
I want to apply log() to my DataFrame and MinMaxScaler() together.
I want the output to be a pandas DataFrame() with indexes and columns from the original data.
I want to use the parameters used to fit_transform() to inverse_transform() res... | https://stackoverflow.com/questions/79167713/how-to-create-a-scaler-applying-log-transformation-and-minmaxscaler-in-sklearn | python, pandas, scikit-learn, data-preprocessing | 1,731,004,869 |
se_79176937 | stackoverflow | MACHINE_LEARNING | Problem in installing and using scikit-learn in Python | Problem in installing and using scikit-learn in Python
I want to run the following code in jupyter-notebook
from sklearn.linear_model import SGDRegressor
before that, I have used the following lines in windows cmd:
python -m venv sklearn-env
sklearn-env\Scripts\activate
pip install -U scikit-learn
But still when I ru... | https://stackoverflow.com/questions/79176937/problem-in-installing-and-using-scikit-learn-in-python | python, scikit-learn, jupyter-notebook, pip, python-venv | 1,731,314,702 |
se_79176191 | stackoverflow | MACHINE_LEARNING | Cannot convert dataframe column to a int64 data type | Cannot convert dataframe column to a int64 data type
I have a problem.
In my Pandas DataFrame, I have a column called 'job' column. I've created a simple and custom transformer that will map values in that column that corresponds to the type of job. The problem arises when after mapping the values and inspecting it, t... | https://stackoverflow.com/questions/79176191/cannot-convert-dataframe-column-to-a-int64-data-type | python, python-3.x, pandas, dataframe, scikit-learn | 1,731,290,401 |
se_50013828 | stackoverflow | MACHINE_LEARNING | ScikitLearn model giving 'LocalOutlierFactor' object has no attribute 'predict' Error | ScikitLearn model giving 'LocalOutlierFactor' object has no attribute 'predict' Error
I'm new to machine learning world and I have built and trained a ml model using ScikitLearn library.It works perfectly well in the Jupyter notebook but when I deployed this model to Google Cloud ML and try to serve it... | https://stackoverflow.com/questions/50013828/scikitlearn-model-giving-localoutlierfactor-object-has-no-attribute-predict | python, scikit-learn, google-cloud-platform, google-cloud-ml | 1,524,628,608 |
se_59435472 | stackoverflow | MACHINE_LEARNING | Implementing Bag of Words in scikit-learn | Implementing Bag of Words in scikit-learn
from sklearn.feature_extraction.text import CountVectorizer
import pandas as pd
headers = ['label', 'sms_message']
df = pd.read_csv ('spam.csv', names = headers)
df ['label'] = df['label'].map({'ham': 0, 'spam': 1})
print (df.head(7))
print (df.shape)
count_vector = CountVecto... | https://stackoverflow.com/questions/59435472/implementing-bag-of-words-in-scikit-learn | python, scikit-learn | 1,576,924,957 |
se_42993550 | stackoverflow | MACHINE_LEARNING | GridSearchCV - XGBoost - Early Stopping | GridSearchCV - XGBoost - Early Stopping
i am trying to do hyperparemeter search with using scikit-learn's GridSearchCV on XGBoost. During gridsearch i'd like it to early stop, since it reduce search time drastically and (expecting to) have better results on my prediction/regression task. I am using XGBoost via its Sci... | https://stackoverflow.com/questions/42993550/gridsearchcv-xgboost-early-stopping | python-3.x, scikit-learn, regression, data-science, xgboost | 1,490,339,703 |
se_78874263 | stackoverflow | MACHINE_LEARNING | Error get_features_name_out in getting back the feature name | Error get_features_name_out in getting back the feature name
I want to know the feature importance to my data, so I use permutation_importance. When I get the result, it seems the feature already decoded, and I want to know the name of my feauture using get_features_name_out. It turns an error 'StandardScaler' object ... | https://stackoverflow.com/questions/78874263/error-get-features-name-out-in-getting-back-the-feature-name | python, pandas, scikit-learn, data-science | 1,723,710,687 |
se_79170289 | stackoverflow | MACHINE_LEARNING | Columns are missing after imputing and creating dummy variables. How should I fix this? | Columns are missing after imputing and creating dummy variables. How should I fix this?
In short: My columns are different between train set and test set after imputing.
Code of making train, test dataset
random_state_value = 0
#Define target
X = data.drop(columns = 'income', axis=1)
y = data['income']
#Split
X_trai... | https://stackoverflow.com/questions/79170289/columns-are-missing-after-imputing-and-creating-dummy-variables-how-should-i-fi | python, machine-learning, scikit-learn | 1,731,073,596 |
se_79169993 | stackoverflow | MACHINE_LEARNING | How to get scikit-learn to ensure that all prediction outputs should sum to 100%? | How to get scikit-learn to ensure that all prediction outputs should sum to 100%?
I have a 'MultiOutputRegressor' which is based on a 'LinearRegression' regressor.
I am using it to predict three outputs per row of X_data (like a classifier) which represent the percentage likelihood of three outcomes.
The regressor is ... | https://stackoverflow.com/questions/79169993/how-to-get-scikit-learn-to-ensure-that-all-prediction-outputs-should-sum-to-100 | python, scikit-learn, output, linear-regression | 1,731,067,972 |
se_70345909 | stackoverflow | MACHINE_LEARNING | Implementing GridSearchCV and Pipelines to perform Hyperparameters Tuning for KNN Algorithm | Implementing GridSearchCV and Pipelines to perform Hyperparameters Tuning for KNN Algorithm
I have been reading about perfroming Hyperparameters Tuning for KNN Algorthim, and understood that the best practice of implementing it is to make sure that for each fold, my dataset should be normalized and oversamplmed using ... | https://stackoverflow.com/questions/70345909/implementing-gridsearchcv-and-pipelines-to-perform-hyperparameters-tuning-for-kn | python, machine-learning, scikit-learn, gridsearchcv, rapids | 1,639,470,986 |
se_79165974 | stackoverflow | MACHINE_LEARNING | how do i set ‘random_state’ correctly so that my results are always the same? | how do i set ‘random_state’ correctly so that my results are always the same?
If I have for example this snippet of code:
knn = KNeighborsClassifier()
grid_search_knn = GridSearchCV(
estimator=knn,
n_jobs=-1)
Do I have to set it like this:
knn = KNeighborsClassifier(random_state=42)
grid_search_knn = GridSea... | https://stackoverflow.com/questions/79165974/how-do-i-set-random-state-correctly-so-that-my-results-are-always-the-same | python, machine-learning, scikit-learn | 1,730,974,676 |
se_56549270 | stackoverflow | MACHINE_LEARNING | ImportError: cannot import name 'MultiOutputMixin' from 'sklearn.base' | ImportError: cannot import name 'MultiOutputMixin' from 'sklearn.base'
I want to do a linear regression with scikit-learn. When I try to import the linear model package the error message from the title appears.
I tried to follow the solution from a similar problem. The suggestion is basically to just g... | https://stackoverflow.com/questions/56549270/importerror-cannot-import-name-multioutputmixin-from-sklearn-base | python, scikit-learn | 1,560,275,566 |
se_57629912 | stackoverflow | MACHINE_LEARNING | How to do cross validation and grid search if I have a customized ensemble model in python pipeline | How to do cross validation and grid search if I have a customized ensemble model in python pipeline
I am building a customized ensemble model and would like to do cross validation and grid search in python using pipeline. How can I do it?
I have a data set contains web content. What I want to do is
Split the content ... | https://stackoverflow.com/questions/57629912/how-to-do-cross-validation-and-grid-search-if-i-have-a-customized-ensemble-model | python, scikit-learn, cross-validation, grid-search, ensemble-learning | 1,566,577,260 |
se_73488178 | stackoverflow | MACHINE_LEARNING | Pipeline for more than 2 classifiers | Pipeline for more than 2 classifiers
I am trying to build an ensemble using Knn and random forest classifiers.
steps = [('scaler', StandardScaler()),
('regressor', VotingClassifier(estimators=[
('knn', KNeighborsClassifier()),
('clf', RandomForestClassifier())]))]
pipeline = Pipeline(steps)
parameters ... | https://stackoverflow.com/questions/73488178/pipeline-for-more-than-2-classifiers | python-3.x, scikit-learn, random-forest, knn, scikit-learn-pipeline | 1,661,433,279 |
se_79162743 | stackoverflow | MACHINE_LEARNING | scikit-learn classifiers and regressors caching training data? | scikit-learn classifiers and regressors caching training data?
I have some 22,000 rows of training data.
I use train_test_split to get training and testing data.
I run fitting and then get some idea of how well fitting went using various methods or estimation.
I want to have the fitted model go back over the 22,000 ro... | https://stackoverflow.com/questions/79162743/scikit-learn-classifiers-and-regressors-caching-training-data | python, scikit-learn, model-fitting | 1,730,898,765 |
se_56420730 | stackoverflow | MACHINE_LEARNING | Cannot Reproduce the Splitting of Train and Test using sklearn | Cannot Reproduce the Splitting of Train and Test using sklearn
I am using Jupyter Notebook version 5.6.0 through the Anaconda Navigator. I am trying to split my dataset to Train and Test but whenever I shutdown and reopen my notebook and rerun the code, it creates a different training and test set. The random_state wo... | https://stackoverflow.com/questions/56420730/cannot-reproduce-the-splitting-of-train-and-test-using-sklearn | python, scikit-learn, split | 1,559,531,697 |
se_53648699 | stackoverflow | MACHINE_LEARNING | Scikit train_test_split by an index | Scikit train_test_split by an index
I have a pandas dataframe indexed by date. Let's assume it from Jan-1 to Jan-30. I want to split this dataset into X_train, X_test, y_train, y_test but I don't want to mix the dates so I want the train and test samples to be divided by a certain date (or index). I'm trying
X_train, ... | https://stackoverflow.com/questions/53648699/scikit-train-test-split-by-an-index | python, pandas, scikit-learn, classification | 1,544,090,211 |
se_79151805 | stackoverflow | MACHINE_LEARNING | Why is my data not getting properly concatenated? | Why is my data not getting properly concatenated?
I split the data using train_test_split after preprocessing:
from sklearn.model_selection import train_test_split
X_train,X_test,y_train,y_test= train_test_split(X,y,test_size=0.2,random_state=42)
Then did robust scaling separately for the numerical columns in test an... | https://stackoverflow.com/questions/79151805/why-is-my-data-not-getting-properly-concatenated | pandas, dataframe, scikit-learn, concatenation, scaling | 1,730,592,385 |
se_79154123 | stackoverflow | MACHINE_LEARNING | How to apply the exported sklearn trained tree to the test data | How to apply the exported sklearn trained tree to the test data
from sklearn.tree import DecisionTreeRegressor, export_text
cols_X = ['f1', 'f2']
df_train = pd.DataFrame([[1, 3, 4], [2, 5, 1], [7, 8, 7]], columns=['f1', 'f2', 'label'])
df_test = pd.DataFrame([[2, 5], [3, 1]], columns=cols_X)
tree = DecisionTreeRegre... | https://stackoverflow.com/questions/79154123/how-to-apply-the-exported-sklearn-trained-tree-to-the-test-data | scikit-learn, decision-tree | 1,730,690,694 |
se_14863125 | stackoverflow | MACHINE_LEARNING | sklearn logistic regression with unbalanced classes | sklearn logistic regression with unbalanced classes
I'm solving a classification problem with sklearn's logistic regression in python.
My problem is a general/generic one. I have a dataset with two classes/result (positive/negative or 1/0), but the set is highly unbalanced. There are ~5% positives and ~95% negative... | https://stackoverflow.com/questions/14863125/sklearn-logistic-regression-with-unbalanced-classes | python, scikit-learn, classification | 1,360,789,584 |
se_50639464 | stackoverflow | MACHINE_LEARNING | Explained variance from scikit-learn MDS | Explained variance from scikit-learn MDS
Is there a way to calculate the explained variance (eigenvalues) from scikit learn's MDS? I've seen this thread, but I think scikit learn's MDS is a "non-classical" form of MDS, so I'm guessing it wouldn't work? Is there a way to compute the explained variance from running scik... | https://stackoverflow.com/questions/50639464/explained-variance-from-scikit-learn-mds | python, scikit-learn | 1,527,842,770 |
se_79134937 | stackoverflow | MACHINE_LEARNING | How to apply multiple estimator on multiple number of features to select the combination with highest f1 score? | How to apply multiple estimator on multiple number of features to select the combination with highest f1 score?
I would like to run recursive feature elimination with multiple estimator algorithms on multiple number of features and keep the highest f1 score combination on the test data.
Instead of reviewing the result... | https://stackoverflow.com/questions/79134937/how-to-apply-multiple-estimator-on-multiple-number-of-features-to-select-the-com | python, machine-learning, scikit-learn, classification, rfe | 1,730,145,440 |
se_79095328 | stackoverflow | MACHINE_LEARNING | Numpy dependency error when using sklearn-1.5:10 environment to deploy Azure ML model | Numpy dependency error when using sklearn-1.5:10 environment to deploy Azure ML model
I'm using the sklearn-1.5(version 10) environment to deploy a ML model which uses sklearn.ensemble._forest.RandomForestClassifier. When deploying the endpoint I keep running into dependency issues with numpy.
I specifically get the f... | https://stackoverflow.com/questions/79095328/numpy-dependency-error-when-using-sklearn-1-510-environment-to-deploy-azure-ml | azure, scikit-learn, deployment, endpoint, ml-studio | 1,729,102,497 |
se_79156832 | stackoverflow | MACHINE_LEARNING | Weird info ordering in scikit-learn trees | Weird info ordering in scikit-learn trees
When plotting scikit-learn trees (on iris data as an example), as in the below code:
from sklearn.datasets import load_iris
from sklearn import tree
iris = load_iris()
X, y = iris.data, iris.target
clf = tree.DecisionTreeClassifier()
clf = clf.fit(X, y)
tree.plot_tree(clf)
e... | https://stackoverflow.com/questions/79156832/weird-info-ordering-in-scikit-learn-trees | scikit-learn, decision-tree | 1,730,750,344 |
se_77528037 | stackoverflow | MACHINE_LEARNING | RuntimeError: Failed to import transformers.models.clip.processing_clip because of the following error | RuntimeError: Failed to import transformers.models.clip.processing_clip because of the following error
RuntimeError: Failed to import transformers.models.clip.processing_clip because of the following error (look up to see its traceback):
[Errno 2] No such file or directory: 'C:\\Users\\xxx\\AppData\\Local\\Temp\\_MEI1... | https://stackoverflow.com/questions/77528037/runtimeerror-failed-to-import-transformers-models-clip-processing-clip-because | python, scikit-learn, pyinstaller, sentence-transformers | 1,700,638,150 |
se_70009445 | stackoverflow | MACHINE_LEARNING | disable internal scikit input validation checks | disable internal scikit input validation checks
Under the hood Scikit-Learn does a lot of input validation checks defined here such as checking for (X,y) shapes, expected scalars/arrays, ensuring estimator is already fitted, etc. When designing models these checks are extremely useful to catch early bugs, but these be... | https://stackoverflow.com/questions/70009445/disable-internal-scikit-input-validation-checks | performance, validation, scikit-learn | 1,637,172,307 |
se_73193085 | stackoverflow | MACHINE_LEARNING | k-NN GridSearchCV taking extremely long time to execute | k-NN GridSearchCV taking extremely long time to execute
I am attempting to use sklearn to train a KNN model on the MNIST classification task. When I try to tune my parameters using either sklearn's GridSearchCV or RandomisedSearchCV classes, my code is taking an extremely long time to execute.
As an experiment, I crea... | https://stackoverflow.com/questions/73193085/k-nn-gridsearchcv-taking-extremely-long-time-to-execute | python, scikit-learn, cross-validation, knn, gridsearchcv | 1,659,354,006 |
se_67428836 | stackoverflow | MACHINE_LEARNING | yellowbrick implementation error - AttributeError: 'LogisticRegression' object has no attribute 'fig' | yellowbrick implementation error - AttributeError: 'LogisticRegression' object has no attribute 'fig'
I am a new user for yellowbrick. While implementing a sklearn LogisticRegression API in yellowbrick ClassificationReport, I found some unusual error. I have tried many syntaxes as suggested by yellowbr... | https://stackoverflow.com/questions/67428836/yellowbrick-implementation-error-attributeerror-logisticregression-object-h | python, scikit-learn, classification, yellowbrick | 1,620,360,085 |
se_79114762 | stackoverflow | MACHINE_LEARNING | How do I onehotencode a single column in a dataframe? | How do I onehotencode a single column in a dataframe?
I have a dataframe called "vehicles" with 8 columns. 7 are numerical but the column named 'Car_name' which is index 1 in the dataframe and is categorical. i need to encode it
i tried this code and wont work
ohe = OneHotEncoding(categorical_features = [1])
vehicl... | https://stackoverflow.com/questions/79114762/how-do-i-onehotencode-a-single-column-in-a-dataframe | python, machine-learning, scikit-learn, one-hot-encoding | 1,729,609,924 |
se_46599534 | stackoverflow | MACHINE_LEARNING | How to find the best value of k For the k-NN? | How to find the best value of k For the k-NN?
I have 4 different datasets and Each dataset contains two-dimensional samples that belong to one of the two classes: 1 or 2. The class labels (1 or 2) for each sample are located in the last column. The first and second columns contain the coordinates of the 2D points that... | https://stackoverflow.com/questions/46599534/how-to-find-the-best-value-of-k-for-the-k-nn | machine-learning, scikit-learn, classification, knn | 1,507,271,182 |
se_68475534 | stackoverflow | MACHINE_LEARNING | SVM model predicts instances with probability scores greater than 0.1(default threshold 0.5) as positives | SVM model predicts instances with probability scores greater than 0.1(default threshold 0.5) as positives
I'm working on a binary classification problem. I had this situation that I used the logistic regression and support vector machine model imported from sklearn. These two models were fit with the same , imbalanced... | https://stackoverflow.com/questions/68475534/svm-model-predicts-instances-with-probability-scores-greater-than-0-1default-th | python, machine-learning, scikit-learn, svm, prediction | 1,626,896,201 |
se_79137908 | stackoverflow | MACHINE_LEARNING | Error when runing mlflow with sklearn model | Error when runing mlflow with sklearn model
I'm training a RandomForestRegressor and keeping track of it using mlflow
Using the following code works perfectly only when n_estimators is lower than 90
The code:
import mlflow
import mlflow.sklearn
from mlflow.models import infer_signature
from sklearn.ensemble import Ran... | https://stackoverflow.com/questions/79137908/error-when-runing-mlflow-with-sklearn-model | python, scikit-learn, mlflow | 1,730,215,845 |
se_78651234 | stackoverflow | MACHINE_LEARNING | How to implement pipeline into machine learning model | How to implement pipeline into machine learning model
I would like to implement Onehot encoding and label encoding to my dataset using Pipeline into my random forest model. I have created a function that utilize pipeline from scikit learn together with OneHotEncoder and LabelEncoder.
def create_pipeline(self, train_fe... | https://stackoverflow.com/questions/78651234/how-to-implement-pipeline-into-machine-learning-model | python, python-3.x, scikit-learn, pipeline, scikit-learn-pipeline | 1,718,958,591 |
se_44041347 | stackoverflow | MACHINE_LEARNING | sklearn: Get Distance from Point to Nearest Cluster | sklearn: Get Distance from Point to Nearest Cluster
I'm using clustering algorithms like DBSCAN.
It returns a 'cluster' called -1 which are points that are not part of any cluster. For these points I want to determine the distance from it to the nearest cluster to get something like a metric for how abnormal this poi... | https://stackoverflow.com/questions/44041347/sklearn-get-distance-from-point-to-nearest-cluster | python, machine-learning, scikit-learn, cluster-analysis, data-mining | 1,495,092,696 |
se_58896645 | stackoverflow | MACHINE_LEARNING | MNIST dataset with Sklearn | MNIST dataset with Sklearn
I’m training linear model on MNIST dataset, but I wanted to train only on one digit that is 4. How do I choose my X_test,X_train, y_test, y_train? | https://stackoverflow.com/questions/58896645/mnist-dataset-with-sklearn | python, scikit-learn, mnist | 1,573,952,929 |
se_65282827 | stackoverflow | MACHINE_LEARNING | How to make predictions with scikit's Surprise? | How to make predictions with scikit's Surprise?
I'm having some trouble understanding the Surprise workflow. I have a file for training (which I seek to split into training and validation), and a file for testing data. I'm having trouble understanding the difference between a Surprise Dataset and Trainset
# Import... | https://stackoverflow.com/questions/65282827/how-to-make-predictions-with-scikits-surprise | python, machine-learning, scikit-learn, recommendation-engine, collaborative-filtering | 1,607,912,384 |
se_31421413 | stackoverflow | MACHINE_LEARNING | How to compute precision, recall, accuracy and f1-score for the multiclass case with scikit learn? | How to compute precision, recall, accuracy and f1-score for the multiclass case with scikit learn?
I'm working in a sentiment analysis problem the data looks like this:
label instances
5 1190
4 838
3 239
1 204
2 127
So my data is unbalanced since 1190 instances are labeled with ... | https://stackoverflow.com/questions/31421413/how-to-compute-precision-recall-accuracy-and-f1-score-for-the-multiclass-case | python, machine-learning, scikit-learn, nlp | 1,436,933,856 |
se_66376105 | stackoverflow | MACHINE_LEARNING | How to perform standardization and normalization on features from different feature engineering process? | How to perform standardization and normalization on features from different feature engineering process?
I'm working with a dataset where each sample contains both numeric and text data. Therefore multiple methods are employed to build the training feature matrix from the dataset. For each sample in the dataset, I con... | https://stackoverflow.com/questions/66376105/how-to-perform-standardization-and-normalization-on-features-from-different-feat | python, machine-learning, scikit-learn, data-science | 1,614,285,530 |
se_62520099 | stackoverflow | MACHINE_LEARNING | Getting error AttributeError: 'bool' object has no attribute 'transpose' when attempting to fit machine learning model | Getting error AttributeError: 'bool' object has no attribute 'transpose' when attempting to fit machine learning model
I am trying to create a machine learning model to predict who would survive on the Titanic. Everytime I try to fit my model, I get this error :
coordinates = np.where(mask.transpos... | https://stackoverflow.com/questions/62520099/getting-error-attributeerror-bool-object-has-no-attribute-transpose-when-at | python, pandas, machine-learning, scikit-learn, model | 1,592,846,671 |
se_55786860 | stackoverflow | MACHINE_LEARNING | How is the hidden layer size determined for MLPRegressor in SciKitLearn? | How is the hidden layer size determined for MLPRegressor in SciKitLearn?
Lets say I'm creating a neural net using the following code:
from sklearn.neural_network import MLPRegressor
model = MLPRegressor(
hidden_layer_sizes=(100,),
activation='identity'
)
model.fit(X_train, y_train)
For the hidden_layer_sizes, ... | https://stackoverflow.com/questions/55786860/how-is-the-hidden-layer-size-determined-for-mlpregressor-in-scikitlearn | python, machine-learning, scikit-learn, neural-network | 1,555,881,701 |
se_79124570 | stackoverflow | MACHINE_LEARNING | How can I install scikit-learn from source using my locally modified clone | How can I install scikit-learn from source using my locally modified clone
I have made modifications to the scikit-learn codebase that I want to test locally, but when I run pytest, I get the error "scikit-learn is not built correctly".
So I try to build it by following the developer instructions, by using this
$ pip ... | https://stackoverflow.com/questions/79124570/how-can-i-install-scikit-learn-from-source-using-my-locally-modified-clone | python, visual-c++, scikit-learn, pypi | 1,729,839,102 |
se_45758280 | stackoverflow | MACHINE_LEARNING | Fast ICA using scikit learn- reconstruction error analysis | Fast ICA using scikit learn- reconstruction error analysis
I am trying to use fastICA procedure in scikitLearn. For validation purposes I tried to understand the difference between PCA and ICA based signal reconstruction.
The original number of observed signals are 6 and I tried to use 3 reconstruction independent c... | https://stackoverflow.com/questions/45758280/fast-ica-using-scikit-learn-reconstruction-error-analysis | machine-learning, scikit-learn, pca, dimensionality-reduction | 1,503,064,097 |
se_23045318 | stackoverflow | MACHINE_LEARNING | grid search over multiple classifiers | grid search over multiple classifiers
Is there a better inbuilt way to do grid search and test multiple models in a single pipeline? Of course the parameters of the models would be different, which made is complicated for me to figure this out. Here is what I did:
from sklearn.pipeline import Pipeline
from sklearn.e... | https://stackoverflow.com/questions/23045318/grid-search-over-multiple-classifiers | python, scikit-learn | 1,397,406,977 |
se_78521298 | stackoverflow | MACHINE_LEARNING | circumvent 250mb layer limit | circumvent 250mb layer limit
I've a python serverless project that relies on scikit-learn, pandas, numpy and sqlachemy.
Combined size of these package is around 350MB which is 100MB more than allowed layer size. Is there any way to use serverless lambdas and provide these packages runtime?
is there a way to optimize p... | https://stackoverflow.com/questions/78521298/circumvent-250mb-layer-limit | amazon-web-services, numpy, scikit-learn, pip, aws-serverless | 1,716,445,814 |
se_20841167 | stackoverflow | MACHINE_LEARNING | How to predict time series in scikit-learn? | How to predict time series in scikit-learn?
Scikit-learn utilizes a very convenient approach based on fit and predict methods. I have time-series data in the format suited for fit and predict.
For example I have the following Xs:
[[1.0, 2.3, 4.5], [6.7, 2.7, 1.2], ..., [3.2, 4.7, 1.1]]
and the corresponding ys:
[... | https://stackoverflow.com/questions/20841167/how-to-predict-time-series-in-scikit-learn | python, machine-learning, time-series, scikit-learn | 1,388,412,393 |
se_31379845 | stackoverflow | MACHINE_LEARNING | Forecasting with time series in python | Forecasting with time series in python
I want to predict the next values of a variable Y (c_start) when X (day) represent the time.
As you can see in the picture, i have values for the attribute "c_start" and I would like to predict the next "c_start" values for the next 7 days(for example).
May someone help me? | https://stackoverflow.com/questions/31379845/forecasting-with-time-series-in-python | python, pandas, scikit-learn, time-series | 1,436,779,996 |
se_59843700 | stackoverflow | MACHINE_LEARNING | Train machine learning model with scikit learn for time-series prediction | Train machine learning model with scikit learn for time-series prediction
I need to train a model with scikit-learn to predict possible time for less people in a room.
Here is how my dataset looks like:
Time PeopleCount
---------------------------------------------
2019-12-29 12:40:10 ... | https://stackoverflow.com/questions/59843700/train-machine-learning-model-with-scikit-learn-for-time-series-prediction | python, machine-learning, scikit-learn | 1,579,618,369 |
se_37556600 | stackoverflow | MACHINE_LEARNING | Advice on how to predict future time series data | Advice on how to predict future time series data
I have time series data for different countries and factors, e.g. birth rate for "Afghanistan" for years from 1972 up until 2007 (source).
Goal:
Predict e.g. birth rate for 2008 and 2012
I am familiar with linear regressions, but need some help on how to work with time ... | https://stackoverflow.com/questions/37556600/advice-on-how-to-predict-future-time-series-data | python, machine-learning, scikit-learn, time-series | 1,464,733,321 |
se_30346605 | stackoverflow | MACHINE_LEARNING | Time series forecasting with scikit learn | Time series forecasting with scikit learn
I am trying to set-up a python code for forecasting a time-series, using the SVM model of scikit-learn.
My data contains X values at 30 minute interval for the last 24 hours, and I need to predict y for the next timestamp. Here's what I have set up -
SVR(kernel='linear', C=1e3... | https://stackoverflow.com/questions/30346605/time-series-forecasting-with-scikit-learn | python, scikit-learn, time-series, svm, forecasting | 1,432,116,575 |
se_66538197 | stackoverflow | MACHINE_LEARNING | Precision calculation warning when using GridSearchCV for Logistic Regression | Precision calculation warning when using GridSearchCV for Logistic Regression
I am trying to run GridSearchCV with the LogisticRegression estimator and record the model accuracy, precision, recall, f1 metrics.
However, I get the following error on the precision metric:
Precision is ill-defined and being set to 0.0 due... | https://stackoverflow.com/questions/66538197/precision-calculation-warning-when-using-gridsearchcv-for-logistic-regression | python, scikit-learn, precision, logistic-regression, gridsearchcv | 1,615,242,810 |
se_77396735 | stackoverflow | MACHINE_LEARNING | How to calculate the values at each node in a scikit-learn GradientBoostingRegressor? | How to calculate the values at each node in a scikit-learn GradientBoostingRegressor?
I am trying to manually calculate the values shown at each node of each tree of an ensemble returned by a GradientBoostingRegressor.
So here is how I train the model:
import numpy as np
import matplotlib.pyplot as plt
import pandas a... | https://stackoverflow.com/questions/77396735/how-to-calculate-the-values-at-each-node-in-a-scikit-learn-gradientboostingregre | scikit-learn, gradient-descent, ensemble-learning | 1,698,762,213 |
se_79118016 | stackoverflow | MACHINE_LEARNING | How to preserve data types when working with pandas and sklearn transformers? | How to preserve data types when working with pandas and sklearn transformers?
While working with a large sklearn Pipeline (fit using a DataFrame) I ran into an error that lead back to a wrong data type of my input. The problem occurred on an a single observation coming from an API that is supposed to interface the mod... | https://stackoverflow.com/questions/79118016/how-to-preserve-data-types-when-working-with-pandas-and-sklearn-transformers | python, pandas, scikit-learn | 1,729,688,488 |
se_54899647 | stackoverflow | MACHINE_LEARNING | what is the difference between transformer and estimator in sklearn? | what is the difference between transformer and estimator in sklearn?
I saw both transformer and estimator were mentioned in the sklearn documentation.
Is there any difference between these two words? | https://stackoverflow.com/questions/54899647/what-is-the-difference-between-transformer-and-estimator-in-sklearn | scikit-learn | 1,551,250,326 |
se_79111896 | stackoverflow | MACHINE_LEARNING | Inconsistent numbers of samples error in multi-class / multi-label machine learning model | Inconsistent numbers of samples error in multi-class / multi-label machine learning model
I have a OneVsOne model running fine with textual feature and target fields. To progress to a multi-class model (i.e. with multiple textual feature fields), I believe OneVsRest with Logistic Regression is suitable.
However, when ... | https://stackoverflow.com/questions/79111896/inconsistent-numbers-of-samples-error-in-multi-class-multi-label-machine-learn | pandas, scikit-learn, sampling, multilabel-classification, multiclass-classification | 1,729,548,914 |
se_55981273 | stackoverflow | MACHINE_LEARNING | ZeroDivisionError when using sklearn's BaggingClassifier with GridSearchCV | ZeroDivisionError when using sklearn's BaggingClassifier with GridSearchCV
I'm trying to improve a perfectly working Bernoulli Naive Bayes model with bagging.
But when I try to cross-validate the BaggingClassifier, I get a very unexpected ZeroDivisionError coming from parallel.py.
I've tried to change all the para... | https://stackoverflow.com/questions/55981273/zerodivisionerror-when-using-sklearns-baggingclassifier-with-gridsearchcv | python, scikit-learn, divide-by-zero | 1,556,962,886 |
se_61998081 | stackoverflow | MACHINE_LEARNING | K-Means clustering Hyperparameter Tuning | K-Means clustering Hyperparameter Tuning
I am trying to perform hyperparameter tuning for Spatio-Temporal K-Means clustering by using it in a pipeline with a Decision Tree classifier. The idea is to use K-Means clustering algorithm to generate cluster-distance space matrix and clustered labels which will be then passe... | https://stackoverflow.com/questions/61998081/k-means-clustering-hyperparameter-tuning | python-3.x, machine-learning, scikit-learn, k-means | 1,590,393,286 |
se_52771440 | stackoverflow | MACHINE_LEARNING | GridSearchCV on a working pipeline returns ValueError | GridSearchCV on a working pipeline returns ValueError
I am using GridSearchCV in order to find the best parameters for my pipeline.
My pipeline seems to work well as I can apply:
pipeline.fit(X_train, y_train)
preds = pipeline.predict(X_test)
And I get a decent result.
But GridSearchCV obviously doesn't like somethin... | https://stackoverflow.com/questions/52771440/gridsearchcv-on-a-working-pipeline-returns-valueerror | python, pandas, scikit-learn, scikit-learn-pipeline | 1,539,312,169 |
se_69082803 | stackoverflow | MACHINE_LEARNING | Found input variables with inconsistent number of samples when I processed "titanic" dataset in kaggle | Found input variables with inconsistent number of samples when I processed "titanic" dataset in kaggle
I did a toy kaggle "Titanic" dataset training and followed the instruction of a linkedin video course named" Applied Machine Learning: Algorithms"
when I typed the following codes: the error occured:
lr = L... | https://stackoverflow.com/questions/69082803/found-input-variables-with-inconsistent-number-of-samples-when-i-processed-tita | scikit-learn, gridsearchcv | 1,630,992,467 |
se_67572787 | stackoverflow | MACHINE_LEARNING | AttributeError and TypeError using CustomTransformers | AttributeError and TypeError using CustomTransformers
I am building a model using customized transformers (KeyError: "None of [Index([('A','B','C')] , dtype='object')] are in the [columns]).
When I run the below code, I get an error because of .fit:
---------------------------------------------------------------------... | https://stackoverflow.com/questions/67572787/attributeerror-and-typeerror-using-customtransformers | python, scikit-learn, scikit-learn-pipeline | 1,621,265,675 |
se_78440449 | stackoverflow | MACHINE_LEARNING | 'Pipeline' object has no attribute '_check_fit_params' | 'Pipeline' object has no attribute '_check_fit_params'
from imblearn.over_sampling import SMOTE
from imblearn.under_sampling import RandomUnderSampler
from imblearn.pipeline import Pipeline
# Define features and target
X = df.drop('infected', axis=1)
y = df['infected']
# Split the data into training ... | https://stackoverflow.com/questions/78440449/pipeline-object-has-no-attribute-check-fit-params | python, machine-learning, scikit-learn, imblearn | 1,715,062,354 |
se_79092031 | stackoverflow | MACHINE_LEARNING | Python Regime Labeling Using Explicit Threshold for Increase/Decrease from peak to trough | Python Regime Labeling Using Explicit Threshold for Increase/Decrease from peak to trough
I am trying to find the longest stretches of time in a time series where the value from start to end increases by at least a certain threshold without any declines in the interim by at least that threshold. Think of the time seri... | https://stackoverflow.com/questions/79092031/python-regime-labeling-using-explicit-threshold-for-increase-decrease-from-peak | python, scikit-learn, scipy, time-series | 1,729,035,059 |
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