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_64742811 | stackoverflow | MACHINE_LEARNING | How to understand SHAP value for an autoencoder model? | How to understand SHAP value for an autoencoder model?
What does 'feature importance' mean for an autoencoder (AE) model?
Suppose I have a well-trained AE model. If I run the code something like
e = shap.KernelExplainer(autoencoder.predict, X_train.values)
shap_values = e.shap_values(X_train.values)
shap.summary_plot(... | https://stackoverflow.com/questions/64742811/how-to-understand-shap-value-for-an-autoencoder-model | machine-learning, autoencoder, shap | 1,604,867,901 |
se_70988481 | stackoverflow | MACHINE_LEARNING | How are SHAP's feature contributions calculated for models with word embeddings as output? | How are SHAP's feature contributions calculated for models with word embeddings as output?
In a typical Shapley value estimation for a numerical regression task, there is a clear way in which the marginal contribution of an input feature i to the final numerical output variable can be calculated. For input feature... | https://stackoverflow.com/questions/70988481/how-are-shaps-feature-contributions-calculated-for-models-with-word-embeddings | machine-learning, neural-network, shap, machine-translation | 1,643,986,748 |
se_52252442 | stackoverflow | MACHINE_LEARNING | How to handle Shift in Forecasted value | How to handle Shift in Forecasted value
I implemented a forecasting model using LSTM in Keras. The dataset is 15mints seperated and I am forecasting for 12 future steps.
The model performs good for the problem. But there is a small problem with the forecast made. It is showing a small shift effect. To get a more cle... | https://stackoverflow.com/questions/52252442/how-to-handle-shift-in-forecasted-value | python, machine-learning, keras, deep-learning, forecasting | 1,536,562,128 |
se_79474519 | stackoverflow | MACHINE_LEARNING | Runtime Error while trying to train RTDetrV2 with Transformer | Runtime Error while trying to train RTDetrV2 with Transformer
I am trying to train RTDetrV2 for detection on water meter digit. I use an ipynb file form here https://colab.research.google.com/github/roboflow-ai/notebooks/blob/main/notebooks/train-rt-detr-on-custom-dataset-with-transformers.ipynb#scrollTo=a7kZr8OtGkIO.... | https://stackoverflow.com/questions/79474519/runtime-error-while-trying-to-train-rtdetrv2-with-transformer | python, machine-learning, pytorch, huggingface-transformers, roboflow | 1,740,717,329 |
se_45909024 | stackoverflow | MACHINE_LEARNING | Using the dev set or the train set | Using the dev set or the train set
Can someone clear up this doubt of mine.
While evaluating the model, we should try a smaller set. the dev set is a small set. So we try something on the dev set and come to a conclusion and then go to the train set to train it properly and check.
OR
We train the training set and e... | https://stackoverflow.com/questions/45909024/using-the-dev-set-or-the-train-set | machine-learning, deep-learning | 1,503,865,495 |
se_78604530 | stackoverflow | MACHINE_LEARNING | Predict.boosting problem: newmfinal must be 1<newmfinal<mfinal | Predict.boosting problem: newmfinal must be 1<newmfinal<mfinal
I'm trying to perform a prediction with the Adaboost algorithm using the predict.boosting() function of the adabag package, but an error occurs:
"Error in predict.boosting(adaboost, train01_new, newmfinal = 9) :
newmfinal must be 1<newmfinal<mfinal"... | https://stackoverflow.com/questions/78604530/predict-boosting-problem-newmfinal-must-be-1newmfinalmfinal | r, machine-learning, adaboost, boosting | 1,718,053,742 |
se_79471261 | stackoverflow | MACHINE_LEARNING | BigQuery ML Time Series model evaluate keeps returning null | BigQuery ML Time Series model evaluate keeps returning null
I’m using BigQuery ML to train an ARIMA_PLUS model for forecasting CPU usage. The model trains successfully, but when I run ML.EVALUATE, all result values are NULL.
Model Training Query
CREATE OR REPLACE MODEL `project.dataset.arima_model`
OPTIONS(
MODEL_TY... | https://stackoverflow.com/questions/79471261/bigquery-ml-time-series-model-evaluate-keeps-returning-null | machine-learning, google-bigquery, time-series, arima | 1,740,612,563 |
se_79471646 | stackoverflow | MACHINE_LEARNING | In ordinal encoder what does handle_unknown= use_encoded_values do? | In ordinal encoder what does handle_unknown= use_encoded_values do?
I've done my research about but I'm not satisfied with the answer I looked up both on the documentation and gemini. use_encoded_value what does it mean? Do I have to pass an argument to act as an encoded values? If so could you give an example on its ... | https://stackoverflow.com/questions/79471646/in-ordinal-encoder-what-does-handle-unknown-use-encoded-values-do | machine-learning, scikit-learn, ordinal-classification | 1,740,632,959 |
se_79475986 | stackoverflow | MACHINE_LEARNING | Pipeline FutureWarning: This Pipeline instance is not fitted yet | Pipeline FutureWarning: This Pipeline instance is not fitted yet
I am working on a fairly simple machine learning problem in the form of a practicum. I am using the following code to preprocess the data:
from preprocess.date_converter import DateConverter
from sklearn.pipeline import Pipeline
from preprocess.nan_fixer... | https://stackoverflow.com/questions/79475986/pipeline-futurewarning-this-pipeline-instance-is-not-fitted-yet | python, machine-learning, scikit-learn, scikit-learn-pipeline | 1,740,756,311 |
se_79478810 | stackoverflow | MACHINE_LEARNING | How Come Memory Footprint of a Tensorflow Model is Increasing After tflite Conversion? | How Come Memory Footprint of a Tensorflow Model is Increasing After tflite Conversion?
Trained a simple tensorflow model containing some LSTM and Dense feed-forward layers. After training, I am quantising and converting the model to a tf.lite format for edge deployment. Here is the relevant part of the code.
...
model... | https://stackoverflow.com/questions/79478810/how-come-memory-footprint-of-a-tensorflow-model-is-increasing-after-tflite-conve | python, tensorflow, machine-learning, tflite | 1,740,905,049 |
se_60591577 | stackoverflow | MACHINE_LEARNING | will dropout layer enhance accuracy | will dropout layer enhance accuracy
I know that adding a dropout layer into a CNN model enhances accuracy, since it decrease the impact of over-fitting. However, I built a CNN model with 16,32 and 64 filters, size 3 and maxpool of 2 and noticed that the model without the dropout layer performed better than the model w... | https://stackoverflow.com/questions/60591577/will-dropout-layer-enhance-accuracy | python, machine-learning, artificial-intelligence, conv-neural-network | 1,583,697,843 |
se_44497187 | stackoverflow | MACHINE_LEARNING | Why are weights and biases necessary in Neural networks? | Why are weights and biases necessary in Neural networks?
Regarding neural networks, why do we need weights and biases?
For weights I've had this intuition that we're trying to multiply certain constants to the inputs such that we could reach the value of y and know the relation, kinda' like y = mx + c. Please help me ... | https://stackoverflow.com/questions/44497187/why-are-weights-and-biases-necessary-in-neural-networks | machine-learning, tensorflow, neural-network | 1,497,263,255 |
se_78171263 | stackoverflow | MACHINE_LEARNING | In Gradient Descent algorithm, how to induce -2*wx | In Gradient Descent algorithm, how to induce -2*wx
part of Gradient Descent algorithm
this.updateWeights = function() {
let wx;
let w_deriv = 0;
let b_deriv = 0;
for (let i = 0; i < this.points; i++) {
wx = this.yArr[i] - (this.weight * this.xArr[i] + this.bias);
w_deriv += -2 * wx * this.xArr[i];
... | https://stackoverflow.com/questions/78171263/in-gradient-descent-algorithm-how-to-induce-2wx | javascript, machine-learning, gradient-descent | 1,710,582,081 |
se_56115874 | stackoverflow | MACHINE_LEARNING | How to convert bounding box (x1, y1, x2, y2) to YOLO Style (X, Y, W, H) | How to convert bounding box (x1, y1, x2, y2) to YOLO Style (X, Y, W, H)
I'm training a YOLO model, I have the bounding boxes in this format:-
x1, y1, x2, y2 => ex (100, 100, 200, 200)
I need to convert it to YOLO format to be something like:-
X, Y, W, H => 0.436262 0.474010 0.383663 0.178218
I already calculated the... | https://stackoverflow.com/questions/56115874/how-to-convert-bounding-box-x1-y1-x2-y2-to-yolo-style-x-y-w-h | machine-learning, math, image-processing, computer-vision, yolo | 1,557,762,732 |
se_67236791 | stackoverflow | MACHINE_LEARNING | Asking advice on EEG classification using Keras | Asking advice on EEG classification using Keras
I have a dataset on EEG, with this shape:
(11,1158, 200)
Where
11 is the number of EEG channel
1158 is the number of each task
200 is the time interval of each task
for example, if you plot a task, you'll get (Note that the data is normalized):
This task represents a ... | https://stackoverflow.com/questions/67236791/asking-advice-on-eeg-classification-using-keras | python, tensorflow, machine-learning, keras | 1,619,211,711 |
se_72754217 | stackoverflow | MACHINE_LEARNING | FastAPI: Internal Server Error when returning ML model prediction | FastAPI: Internal Server Error when returning ML model prediction
I would like to test my pipeline in FastAPI, but I can't find the mistake in my code. When I test it using the Visual Studio Code (using a print() statement), it works. However, when I try accessing the endpoint through the browser, I get Internal Serve... | https://stackoverflow.com/questions/72754217/fastapi-internal-server-error-when-returning-ml-model-prediction | python, machine-learning, scikit-learn, fastapi, pipeline | 1,656,163,472 |
se_73533170 | stackoverflow | MACHINE_LEARNING | My Neural network is perfroming regression instead of classification | My Neural network is perfroming regression instead of classification
I am working on a Data Science project which requires implementation of a neural network. The dataset I am providing for training is not sequential and has class labels. But I don't know why it is treating it as sequence of events.
I am using the fol... | https://stackoverflow.com/questions/73533170/my-neural-network-is-perfroming-regression-instead-of-classification | python, tensorflow, machine-learning, scikit-learn, neural-network | 1,661,797,668 |
se_79473712 | stackoverflow | MACHINE_LEARNING | Stable torch, ultralytics, tensorflow packages for requirements.txt | Stable torch, ultralytics, tensorflow packages for requirements.txt
I'm writing a requirements.txt for a real-time sports video analysis project and testing various libraries such as YOLOv8, Torch, TensorFlow, etc.
I've tried multiple Python versions but encountered compatibility issues.
Which versions should I instal... | https://stackoverflow.com/questions/79473712/stable-torch-ultralytics-tensorflow-packages-for-requirements-txt | python, numpy, machine-learning, pytorch, ultralytics | 1,740,683,980 |
se_79474503 | stackoverflow | MACHINE_LEARNING | Why does my Keras model show 4 parameters instead of 2? | Why does my Keras model show 4 parameters instead of 2?
I'm training a simple Keras model with one Dense layer, but when I call model.summary(), it shows 4 parameters instead of 2.
import tensorflow as tf
import numpy as np
# Generate dummy data
X_train = np.random.rand(40) # Shape (40,)
y_train = np.random.rand(40)... | https://stackoverflow.com/questions/79474503/why-does-my-keras-model-show-4-parameters-instead-of-2 | python, tensorflow, machine-learning, keras, deep-learning | 1,740,716,331 |
se_78620402 | stackoverflow | MACHINE_LEARNING | Dataloader error in pytorch PascalVOC dataset: RuntimeError: each element in list of batch should be of equal size | Dataloader error in pytorch PascalVOC dataset: RuntimeError: each element in list of batch should be of equal size
When trying to implement the yolo algortithm, one of the steps is to resize each image to (448, 448). But even with the transform applied the Dataloader throw an exception about difference of size in the ... | https://stackoverflow.com/questions/78620402/dataloader-error-in-pytorch-pascalvoc-dataset-runtimeerror-each-element-in-lis | machine-learning, deep-learning, pytorch, yolo, pytorch-dataloader | 1,718,318,629 |
se_79473125 | stackoverflow | MACHINE_LEARNING | How to let PyTorch learn coefficients variables for the loss outside of nn.Module? | How to let PyTorch learn coefficients variables for the loss outside of nn.Module?
I have a combined loss funcation like this:
loss = alpha * loss0 + beta* loss1 + gamma * loss2 + delta* loss3
I would like to make alpha, beta, gamma, and delta learnable parameters. Notice that alpha, beta, gamma, and delta are outsid... | https://stackoverflow.com/questions/79473125/how-to-let-pytorch-learn-coefficients-variables-for-the-loss-outside-of-nn-modul | machine-learning, pytorch | 1,740,669,392 |
se_74239556 | stackoverflow | MACHINE_LEARNING | KeyError: 'eval_loss' in Hugginface Trainer | KeyError: 'eval_loss' in Hugginface Trainer
I am trying to build a Question Answering Pipeline with the Hugginface framework but facing the KeyError: 'eval_loss' error. My goal is to train and save the best model at last and evaluate the validation test on the loaded model. My trainer configuration looks like ... | https://stackoverflow.com/questions/74239556/keyerror-eval-loss-in-hugginface-trainer | python-3.x, machine-learning, pytorch, huggingface-transformers, huggingface-tokenizers | 1,666,981,828 |
se_55290709 | stackoverflow | MACHINE_LEARNING | What does from_logits = True or False mean in sparse_categorical_crossentropy of Tensorflow? | What does from_logits = True or False mean in sparse_categorical_crossentropy of Tensorflow?
In Tensorflow 2.0,
there is a loss function called
tf.keras.losses.sparse_categorical_crossentropy(labels, targets, from_logits = False)
What are the differences between setting from_logits = True or False?
My guess was that ... | https://stackoverflow.com/questions/55290709/what-does-from-logits-true-or-false-mean-in-sparse-categorical-crossentropy-of | tensorflow, machine-learning, loss-function, cross-entropy | 1,553,210,795 |
se_5107371 | stackoverflow | MACHINE_LEARNING | Document Analysis and Tagging | Document Analysis and Tagging
Let's say I have a bunch of essays (thousands) that I want to tag, categorize, etc. Ideally, I'd like to train something by manually categorizing/tagging a few hundred, and then let the thing loose.
What resources (books, blogs, languages) would you recommend for undertaking such a task?... | https://stackoverflow.com/questions/5107371/document-analysis-and-tagging | machine-learning, nlp, classification, bayesian, tagging | 1,298,564,443 |
se_78125296 | stackoverflow | MACHINE_LEARNING | How can I solve the Problem during Mbed compile?(depthwise_conv.cc) | How can I solve the Problem during Mbed compile?(depthwise_conv.cc)
I'm studying about machine learning using tinyML book.
I'm trying to Mbed compile, but it is not working.
The problem situations is the following:
The book proposes the following process.
make -f tensorflow/lite/micro/tools/make/Makefile \
TARGET=mbed... | https://stackoverflow.com/questions/78125296/how-can-i-solve-the-problem-during-mbed-compiledepthwise-conv-cc | machine-learning, mbed, tinyml | 1,709,865,848 |
se_79469831 | stackoverflow | MACHINE_LEARNING | Using binary ({0,1}) weights in a Neural Network layer | Using binary ({0,1}) weights in a Neural Network layer
I want to create a custom linear (not fully connected) layer in Pytorch. What is special in this layer is that I need its weights to be binary (0 or 1), so that this layer acts as a "mask", masking out these features that get a weight of 0. Since backpropagation i... | https://stackoverflow.com/questions/79469831/using-binary-0-1-weights-in-a-neural-network-layer | python, machine-learning, deep-learning, pytorch, neural-network | 1,740,574,940 |
se_79457834 | stackoverflow | MACHINE_LEARNING | Serialization error using ray-tuner for hyperparameter tuning | Serialization error using ray-tuner for hyperparameter tuning
I am trying to tune some hyperparameters for my neural network for an image segmentational problem. I set up the tuner as simple as it can be, but when I run my code i get the following error:
2025-02-21 15:19:59,571 INFO worker.py:1832 -- Started a local R... | https://stackoverflow.com/questions/79457834/serialization-error-using-ray-tuner-for-hyperparameter-tuning | python, machine-learning, serialization, hyperparameters, ray | 1,740,151,118 |
se_44939725 | stackoverflow | MACHINE_LEARNING | Support vector machine overfitting my data | Support vector machine overfitting my data
I am trying to make predictions for the iris dataset. I have decided to use svms for this purpose. But, it gives me an accuracy 1.0. Is it a case of overfitting or is it because the model is very good? Here is my code.
X_train, X_test, y_train, y_test = train_test_split(X, y... | https://stackoverflow.com/questions/44939725/support-vector-machine-overfitting-my-data | python, python-3.x, machine-learning, scikit-learn, svm | 1,499,314,673 |
se_28154839 | stackoverflow | MACHINE_LEARNING | SVM overfitting in scikit learn | SVM overfitting in scikit learn
I am building digit recognition classification using SVM. I have 10000 data and I split them to training and test data with a ratio 7:3. I use linear kernel.
The results turn out that training accuracy is always 1 when change training example numbers, however the test accuracy is just a... | https://stackoverflow.com/questions/28154839/svm-overfitting-in-scikit-learn | machine-learning, scikit-learn, svm | 1,422,291,244 |
se_79467839 | stackoverflow | MACHINE_LEARNING | Unable to get the raw decimal of my weights, auto rounding somewhere? | Unable to get the raw decimal of my weights, auto rounding somewhere?
I'm doing a single layer perceptron where I need to get my model to predict whether the user makes a T or an L using some buttons on a website. rn i'm trying to get the weights and bias so I can implement them into my websites pyscript code since I ... | https://stackoverflow.com/questions/79467839/unable-to-get-the-raw-decimal-of-my-weights-auto-rounding-somewhere | python, machine-learning, weighted, perceptron | 1,740,516,444 |
se_65707204 | stackoverflow | MACHINE_LEARNING | Why is my basic CNN model NOT overfitting segmentation image dataset? | Why is my basic CNN model NOT overfitting segmentation image dataset?
I have a dataset of 2000x256x256x3 RGB images (of pink tissue containing purple/blue nuclei) and corresponding ground truth of size 200x256x256x1. The ground truth images are binary. Now, here is my model (Tensorflow version 1.x and Keras):
def crea... | https://stackoverflow.com/questions/65707204/why-is-my-basic-cnn-model-not-overfitting-segmentation-image-dataset | python, machine-learning, keras, conv-neural-network, image-segmentation | 1,610,560,183 |
se_79465469 | stackoverflow | MACHINE_LEARNING | How do I implement a different type of scheduler after training my DDPM on a linear scheduler? | How do I implement a different type of scheduler after training my DDPM on a linear scheduler?
I trained a Diffusion model (DDPM) using a linear scheduler defined by the following code:
scheduler = DDPMScheduler(
num_train_timesteps=1000,
beta_start=0.0001,
beta_end=0.02,
beta_schedule="linear"
)
Howe... | https://stackoverflow.com/questions/79465469/how-do-i-implement-a-different-type-of-scheduler-after-training-my-ddpm-on-a-lin | python, machine-learning, artificial-intelligence | 1,740,460,449 |
se_79456368 | stackoverflow | MACHINE_LEARNING | How to forecast values with multiple regressors using fbprophet? | How to forecast values with multiple regressors using fbprophet?
I want to forecast hourly temperature values using the fbprophet model. So far I have trained the model on just ds and y variable and it is giving me good results. But now I want to add extra regressors and then perform the forecast.
After fitting the mo... | https://stackoverflow.com/questions/79456368/how-to-forecast-values-with-multiple-regressors-using-fbprophet | python, machine-learning, time-series, forecasting, facebook-prophet | 1,740,113,333 |
se_75693007 | stackoverflow | MACHINE_LEARNING | Pytorch RuntimeError: mat1 & mat2 shapes cannot be multiplied | Pytorch RuntimeError: mat1 & mat2 shapes cannot be multiplied
I am building a CNN on Pytorch and getting the following error message:
RuntimeError: mat1 and mat2 shapes cannot be multiplied (32x32768 and
512x256)
I have built the following model:
def classifier_block(input, output, kernel_size, stride, last_laye... | https://stackoverflow.com/questions/75693007/pytorch-runtimeerror-mat1-mat2-shapes-cannot-be-multiplied | python, machine-learning, deep-learning, pytorch, conv-neural-network | 1,678,430,896 |
se_79463813 | stackoverflow | MACHINE_LEARNING | Autoencoder for multi-label classification task | Autoencoder for multi-label classification task
I'm working on a multi-label classification problem using an autoencoder-based neural network built in PyTorch. The overall idea of my approach is as follows:
I load my dataset from a CSV file, perform cleaning (dropping missing values and unnecessary columns), and selec... | https://stackoverflow.com/questions/79463813/autoencoder-for-multi-label-classification-task | python, machine-learning, pytorch, neural-network, autoencoder | 1,740,406,673 |
se_78759790 | stackoverflow | MACHINE_LEARNING | How do I successfully set and retrieve metadata information for a HuggingfaceDataset on the Huggingface Hub? | How do I successfully set and retrieve metadata information for a HuggingfaceDataset on the Huggingface Hub?
I have a number of datasets, which I create from a dictionary like so:
info = DatasetInfo(
description="my happy lil dataset",
version="0.0.1",
homepage="https://www.myhomepage.co.uk"
... | https://stackoverflow.com/questions/78759790/how-do-i-successfully-set-and-retrieve-metadata-information-for-a-huggingfacedat | python, machine-learning, huggingface, huggingface-datasets | 1,721,222,584 |
se_34611337 | stackoverflow | MACHINE_LEARNING | how to find the nearest neighbor of a sparse vector | how to find the nearest neighbor of a sparse vector
I have about 500 vectors,each vector is a 1500-dimension vector,
and almost every vector is very sparse-- I mean only about 30-70 dimension of the vector is not 0。
Now, the problem is that here is a given vector,also 1500 dimension,and I need to compare it to the 500... | https://stackoverflow.com/questions/34611337/how-to-find-the-nearest-neighbor-of-a-sparse-vector | algorithm, vector, machine-learning, information-retrieval | 1,451,995,621 |
se_71261999 | stackoverflow | MACHINE_LEARNING | How to find contours in dotted text captcha image | How to find contours in dotted text captcha image
I am newbie to OpenCV. I'm trying to find the contours of the captcha image. It does not work only when my captcha image contains the dotted text.
I have done following code for that:
import numpy as np
import cv2 as cv
import imgaug.augmenters as iaa
im = cv.imread('... | https://stackoverflow.com/questions/71261999/how-to-find-contours-in-dotted-text-captcha-image | python, tensorflow, opencv, machine-learning, computer-vision | 1,645,771,172 |
se_47397130 | stackoverflow | MACHINE_LEARNING | What is the minimum size of dataset that get high accuracy on machine learning? | What is the minimum size of dataset that get high accuracy on machine learning?
I'm trying to make an app that gets an image of flower and identifies it.
I thought of using machine learning, but when I looked up for datasets I only found datasets that contain at most 700 images per flower.
I understood that it is not ... | https://stackoverflow.com/questions/47397130/what-is-the-minimum-size-of-dataset-that-get-high-accuracy-on-machine-learning | image-processing, machine-learning, dataset | 1,511,196,754 |
se_79449572 | stackoverflow | MACHINE_LEARNING | Train LSTM for time series with varying lengths | Train LSTM for time series with varying lengths
I'm training a LSTM for time series prediction, where data comes from sensors at irregular intervals. I'm using the last 5 min data to predict the next value, but some sequences are larger than others.
My input array's shape is (611,1200,15) where (sample, timesteps, fea... | https://stackoverflow.com/questions/79449572/train-lstm-for-time-series-with-varying-lengths | machine-learning, keras, time-series, lstm, training-data | 1,739,911,654 |
se_60398211 | stackoverflow | MACHINE_LEARNING | Predicted Image id and box from SSD | Predicted Image id and box from SSD
How to find predicted image id and Box from SSD, I am using this GitHub link here is the test function which I want to save the image id and box
def test(loader, net, criterion, device):
net.eval()
running_loss = 0.0
running_regression_loss = 0.0
running_classificati... | https://stackoverflow.com/questions/60398211/predicted-image-id-and-box-from-ssd | python, machine-learning, deep-learning, pytorch, neural-network | 1,582,644,961 |
se_58306578 | stackoverflow | MACHINE_LEARNING | Training Chip and Target Image format in TensorFlow | Training Chip and Target Image format in TensorFlow
I am trying to build a Land Cover Classification model for Sentinel Image. The Image Channels(bands) I am using are 32-bit float.
I need to understand how to best format the Image data, both the chips/patches for training and the Target Image for Classification. I ha... | https://stackoverflow.com/questions/58306578/training-chip-and-target-image-format-in-tensorflow | tensorflow, machine-learning, keras, training-data, satellite-image | 1,570,631,706 |
se_76220101 | stackoverflow | MACHINE_LEARNING | Comparing the Weights and Biases of several different Yolov8s models trained through transfer learning | Comparing the Weights and Biases of several different Yolov8s models trained through transfer learning
I have 3 different yolov8s models which I would like to assess:
Yolov8s trained with the normal model.train() command
Yolo8vs model trained with a frozen backbone
Yolov8s model trained with all layers frozen
I a... | https://stackoverflow.com/questions/76220101/comparing-the-weights-and-biases-of-several-different-yolov8s-models-trained-thr | python, machine-learning, pytorch, yolo, transfer-learning | 1,683,731,616 |
se_79457237 | stackoverflow | MACHINE_LEARNING | fit function stops after epoch 1 | fit function stops after epoch 1
I have implemented this function to fit the model
def fit_model(model, X_train_sequence_tensor,Y_train_sequence_tensor, epochs, val_set, time_windows, scaler):
X_column_list = [item for item in val_set.columns.to_list() if item not in ['date', 'user', 'rank','rank_group', 'cou... | https://stackoverflow.com/questions/79457237/fit-function-stops-after-epoch-1 | python, machine-learning, deep-learning | 1,740,137,210 |
se_79457437 | stackoverflow | MACHINE_LEARNING | numpy eager execution problem after loading a CNN model | numpy eager execution problem after loading a CNN model
I want to save and load a CNN model to further training. I have developed a model and saved it as .h5 file. There is no problem when creating, training, and saving at first run.
The problem exists when loading an existing .h5 model and attempting to train it. The... | https://stackoverflow.com/questions/79457437/numpy-eager-execution-problem-after-loading-a-cnn-model | python, numpy, tensorflow, machine-learning, keras | 1,740,142,854 |
se_31154748 | stackoverflow | MACHINE_LEARNING | R classification tree with Rpart | R classification tree with Rpart
I have some data which I would like to segment.
My first thought was classification tree in R from Rpart package.
My training data consists of many explanatory variables and one 0-1 response variable named "sold". The response value "1" appears in about 80% of rows.
When I try to build... | https://stackoverflow.com/questions/31154748/r-classification-tree-with-rpart | r, machine-learning, tree, rpart | 1,435,734,700 |
se_46844891 | stackoverflow | MACHINE_LEARNING | How to plot a ROC curve for a SVM model in R | How to plot a ROC curve for a SVM model in R
I have trained and tested a model using the following code
library(e1071)
library(readxl)
library(caret)
class1.svm.model <- svm(Class ~ ., data = class1.trainset,cost=20, cross=10,type="C-classification",kernel="radial",na.action=na.omit)
class1.svm.pred <- predict(class... | https://stackoverflow.com/questions/46844891/how-to-plot-a-roc-curve-for-a-svm-model-in-r | r, machine-learning, svm, roc | 1,508,487,089 |
se_78844279 | stackoverflow | MACHINE_LEARNING | Shapes mismatch while training diffusers/UNet2DConditionModel | Shapes mismatch while training diffusers/UNet2DConditionModel
I am trying to train diffusers/UNet2DConditionModel from scratch. Currently I have error on unet forwarding: mat1 and mat2 shapes cannot be multiplied (288x512 and 1280x512). I noticed that mat1 first dimension (288) can vary depending on dataset batch.
How... | https://stackoverflow.com/questions/78844279/shapes-mismatch-while-training-diffusers-unet2dconditionmodel | machine-learning, pytorch, stable-diffusion, image-generation, diffusers | 1,723,041,326 |
se_79448915 | stackoverflow | MACHINE_LEARNING | Qiskit ImportError | Qiskit ImportError
I was trying to import QuantumKernals using the following:
from qiskit_machine_learning.kernels import QuantumKernel
but i am getting this error:
from qiskit_machine_learning.kernels import QuantumKernel
ImportError: cannot import name 'QuantumKernel' from 'qiskit_machine_learning.kernels'
(C:\Us... | https://stackoverflow.com/questions/79448915/qiskit-importerror | machine-learning, importerror, qiskit | 1,739,894,755 |
se_53603376 | stackoverflow | MACHINE_LEARNING | Calculate AUC manually without using any Numpy or Sklearn library | Calculate AUC manually without using any Numpy or Sklearn library
I have given a set of X, Y coordinate and I need to find the AUC using trapezoidal formula, without using any numpy or sklearn library.
(x0,y0) is always (0,0)
(xn,yn) is always (1,1)
Below diagram
Without using any sklearn library, I understand ... | https://stackoverflow.com/questions/53603376/calculate-auc-manually-without-using-any-numpy-or-sklearn-library | python, machine-learning, auc | 1,543,878,815 |
se_55831235 | stackoverflow | MACHINE_LEARNING | Calculating the Number of flops for a given Neural Network? | Calculating the Number of flops for a given Neural Network?
I have a neural network (ALEXnet or VGG16) written with Keras for Image Classification and I would like to calculate the number of floating point operations for a network. The size of the images in the dataset could vary.
Can a generalized code be written in ... | https://stackoverflow.com/questions/55831235/calculating-the-number-of-flops-for-a-given-neural-network | machine-learning, deep-learning, conv-neural-network, flops | 1,556,112,512 |
se_76248695 | stackoverflow | MACHINE_LEARNING | d2l package installation on google colab | d2l package installation on google colab
I need to intall d2l package with
pip install d2l==1.0.0b0
However, whenever I try to download it to google colab, the following error occurs:
Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/
Collecting d2l==1.0.0-beta0
Using... | https://stackoverflow.com/questions/76248695/d2l-package-installation-on-google-colab | machine-learning, deep-learning, d2l | 1,684,083,575 |
se_79450720 | stackoverflow | MACHINE_LEARNING | Am I chaining neural network wrong? Predictions seem random sometimes | Am I chaining neural network wrong? Predictions seem random sometimes
I'm trying to make neural network with 2 layers(1st have 2 neurons, 2nd have 1 neuron) that looks through the list of 4 numbers, and if the first AND third numbers are equal to 1 then answer should be 1, in other cases = 0.
I dont use any AI framewo... | https://stackoverflow.com/questions/79450720/am-i-chaining-neural-network-wrong-predictions-seem-random-sometimes | python, machine-learning, neural-network | 1,739,954,837 |
se_58395644 | stackoverflow | MACHINE_LEARNING | Convert onnx model to keras | Convert onnx model to keras
I try to convert an ONNX model to Keras, but when I call the conversion function I receive the following error message "TypeError: unhashable type: 'google.protobuf.pyext._message.RepeatedScalarContainer'"
ONNX Model Input: input_1
You can see the ONNX Model here: https://ibb.co/sKnbxWY
... | https://stackoverflow.com/questions/58395644/convert-onnx-model-to-keras | python, machine-learning, keras, onnx | 1,571,145,306 |
se_75475057 | stackoverflow | MACHINE_LEARNING | How to convert a human-readable timeline to table using existing ML tools? | How to convert a human-readable timeline to table using existing ML tools?
I have this timeline from a newspaper produced by my Native American tribe. I was trying to use AWS Textract to produce some kind of table from this. AWS Textract does not recognize any tables in this. So I don't think that will work (perhaps m... | https://stackoverflow.com/questions/75475057/how-to-convert-a-human-readable-timeline-to-table-using-existing-ml-tools | machine-learning, extract, ocr, amazon-textract | 1,676,564,187 |
se_62031683 | stackoverflow | MACHINE_LEARNING | Ragged tensors as input for LSTM | Ragged tensors as input for LSTM
Learning about ragged tensors and how can I use them with tensorflow.
My example
xx = tf.ragged.constant([
[0.1, 0.2],
[0.4, 0.7 , 0.5, 0.6]
])
yy = np.array([[0, 0, 1], [1,0,0]])
mdl = tf.keras.Sequential([
... | https://stackoverflow.com/questions/62031683/ragged-tensors-as-input-for-lstm | tensorflow, machine-learning, keras | 1,590,528,312 |
se_79434756 | stackoverflow | MACHINE_LEARNING | ValueError: X has 7 features, but ColumnTransformer expects 13 features | ValueError: X has 7 features, but ColumnTransformer expects 13 features
I have the following code where I try to predict price of tools for which I use poisson regression.
# --- Load and Prepare Data ---
y = train['PriceToday']
X = train.drop(columns=['PriceToday'])
# Define non-standard types
non_standard_types = ["... | https://stackoverflow.com/questions/79434756/valueerror-x-has-7-features-but-columntransformer-expects-13-features | python, machine-learning, scikit-learn, one-hot-encoding, column-tansformer | 1,739,404,263 |
se_79448585 | stackoverflow | MACHINE_LEARNING | OpenCV: Segmenting/Extracting printer labels from image | OpenCV: Segmenting/Extracting printer labels from image
I have footage of labels coming out of a printer.
I want to extract the individual labels from the frame (i.e., detect the boundaries of each individual label), and then find the distance between the printed rectangle and the label's top edge in mm.
This is a fra... | https://stackoverflow.com/questions/79448585/opencv-segmenting-extracting-printer-labels-from-image | opencv, machine-learning, image-processing, computer-vision | 1,739,888,766 |
se_79447495 | stackoverflow | MACHINE_LEARNING | Is there any difference between these two implementations of LoRA (Low-Rank Adaptation)? | Is there any difference between these two implementations of LoRA (Low-Rank Adaptation)?
We all know that LoRA is a low-rank adaptation method, which can be formulated as follows: x = W_0 * x + (A @ B) * x. I have two different code implementations of this. Are there any differences between them?
Code 1:
def forward(s... | https://stackoverflow.com/questions/79447495/is-there-any-difference-between-these-two-implementations-of-lora-low-rank-adap | machine-learning, pytorch, peft | 1,739,865,416 |
se_79449194 | stackoverflow | MACHINE_LEARNING | Scalability Issue in recommender system | Scalability Issue in recommender system
I'm new to recommender system and I'm currently building a collaborative filtering based recommender system. In my dataset there are current 600 users and 9000 items having different ratings. I have created a user item interaction matrix and I'm doing all my operations in numpy.... | https://stackoverflow.com/questions/79449194/scalability-issue-in-recommender-system | numpy, machine-learning, time-complexity, recommendation-engine | 1,739,901,149 |
se_79445942 | stackoverflow | MACHINE_LEARNING | How to Perform Out-of-Sample Forecast for a Hybrid VAR-LSTM Model? | How to Perform Out-of-Sample Forecast for a Hybrid VAR-LSTM Model?
I have built a hybrid model that combines a Vector Autoregressive (VAR) model and a Long Short-Term Memory (LSTM) network. The VAR model is used to capture linear dependencies between macroeconomic indicators, while the LSTM model is trained on the res... | https://stackoverflow.com/questions/79445942/how-to-perform-out-of-sample-forecast-for-a-hybrid-var-lstm-model | python, machine-learning, lstm, var, forecasting | 1,739,807,791 |
se_77613507 | stackoverflow | MACHINE_LEARNING | Training llm for Query Generation in a Graph Database | Training llm for Query Generation in a Graph Database
If I have developed a graph database which has its own query language. I have to find a way to feed llm the graph and then llm should be able to generate the queries of our database.
I have found something similar in langchain that we can feed it the rdf file and t... | https://stackoverflow.com/questions/77613507/training-llm-for-query-generation-in-a-graph-database | machine-learning, nlp, sparql, langchain, large-language-model | 1,701,869,646 |
se_70853882 | stackoverflow | MACHINE_LEARNING | Azure Machine Learning | Azure Machine Learning
I can create a machine learning workspace in azure, because I cant choose a region.
Can you help me please?
Error | https://stackoverflow.com/questions/70853882/azure-machine-learning | azure, machine-learning | 1,643,135,549 |
se_79439462 | stackoverflow | MACHINE_LEARNING | How to train sklearn model in different Dataframes? | How to train sklearn model in different Dataframes?
I have a ML model made with "knn" in scikit-learn and noticed that the more i have data, more precise my model is getting with it's predictions. The problem is, i have lot's of DataFrames that show different situations for the same system i want to predict. Is it pos... | https://stackoverflow.com/questions/79439462/how-to-train-sklearn-model-in-different-dataframes | python, machine-learning, scikit-learn | 1,739,538,105 |
se_53416245 | stackoverflow | MACHINE_LEARNING | Best model type in TensorFlow.js for Color Prediction? | Best model type in TensorFlow.js for Color Prediction?
I was creating a color predictor when I realized a problem arise. I got the model to work successfully, but the predictions are always within the same median range of about 2.5 to about 5.5. The model is supposed to output a 0 thru 8 corresponding to each color, a... | https://stackoverflow.com/questions/53416245/best-model-type-in-tensorflow-js-for-color-prediction | javascript, tensorflow, machine-learning, tensorflow.js | 1,542,816,843 |
se_76020437 | stackoverflow | MACHINE_LEARNING | Trouble unscaling data after predictions | Trouble unscaling data after predictions
I am working on a project where I am trying to predict mlb player stats from 1970 - 2022. I have 2 datasets, one for batters where I am predicting on 5 stats with 20 features and another for pitchers where I am predicting on 6 stats with 25 features. I am currently working on a... | https://stackoverflow.com/questions/76020437/trouble-unscaling-data-after-predictions | python, machine-learning, scikit-learn, decision-tree | 1,681,534,854 |
se_71996617 | stackoverflow | MACHINE_LEARNING | Invalid classes inferred from unique values of `y`. Expected: [0 1 2 3 4 5], got [1 2 3 4 5 6] | Invalid classes inferred from unique values of `y`. Expected: [0 1 2 3 4 5], got [1 2 3 4 5 6]
I've trained dataset using XGB Classifier, but I got this error in local. It worked on Colab and also my friends don't have any problem with same code.
I don't know what that error means...
Invalid classes inferred from uniq... | https://stackoverflow.com/questions/71996617/invalid-classes-inferred-from-unique-values-of-y-expected-0-1-2-3-4-5-got | python, machine-learning, classification, xgboost, xgbclassifier | 1,650,875,558 |
se_79417285 | stackoverflow | MACHINE_LEARNING | Error in predict.train .... type must be either "raw" or "prob" | Error in predict.train .... type must be either "raw" or "prob"
I am using caret with ranger for regression but I need to set quantreg = TRUE as I need this to compute quantiles (see below) some extract of my code. But I am getting this error:
Error in predict.train(object = rf_fit, data = df_test... | https://stackoverflow.com/questions/79417285/error-in-predict-train-type-must-be-either-raw-or-prob | r, machine-learning, regression, caret | 1,738,832,198 |
se_48938905 | stackoverflow | MACHINE_LEARNING | return the labels and their encoded values in sklearn LabelEncoder | return the labels and their encoded values in sklearn LabelEncoder
I'm using LabelEncoder and OneHotEncoder from sklearn in a Machine Learning project to encode the labels (country names) in the dataset. Everything works good and my model runs perfectly. The project is to classify whether a bank customer will continue... | https://stackoverflow.com/questions/48938905/return-the-labels-and-their-encoded-values-in-sklearn-labelencoder | python, machine-learning, scikit-learn, one-hot-encoding | 1,519,342,082 |
se_79440021 | stackoverflow | MACHINE_LEARNING | theta values for gradient descent not coherent | theta values for gradient descent not coherent
i made a gradient descent code but it doesnt seem to work well
import numpy as np
from random import randint,random
import matplotlib . pyplot as plt
def calculh(theta, X):
h = 0
h+=theta[0]*X # w*X
h+= theta[-1] # +b
return h
def calculY(sigma, h) :
... | https://stackoverflow.com/questions/79440021/theta-values-for-gradient-descent-not-coherent | python, machine-learning, artificial-intelligence, gradient-descent, cost-based-optimizer | 1,739,551,283 |
se_79442381 | stackoverflow | MACHINE_LEARNING | Implementing a perceptron using numpy | Implementing a perceptron using numpy
I'm trying to implement a perceptron in python using numpy, when using the notation z=XW+b everything is fine. While studying ML I do see though that z=WX+b is also common, especially when talking about neural networks. The problem is that the dimensions of the matrices don't add ... | https://stackoverflow.com/questions/79442381/implementing-a-perceptron-using-numpy | python, numpy, machine-learning, neural-network, perceptron | 1,739,661,917 |
se_79420818 | stackoverflow | MACHINE_LEARNING | Clearing tf.data.Dataset from GPU memory | Clearing tf.data.Dataset from GPU memory
I'm running into an issue when implementing a training loop that uses a tf.data.Dataset as input to a Keras model. My dataset has an element spec of the following format:
({'data': TensorSpec(shape=(15000, 1), dtype=tf.float32), 'index': TensorSpec(shape=(2,), dtype=tf.int64)},... | https://stackoverflow.com/questions/79420818/clearing-tf-data-dataset-from-gpu-memory | python, tensorflow, machine-learning, keras | 1,738,929,732 |
se_79429107 | stackoverflow | MACHINE_LEARNING | How can I resolve "RuntimeError: The size of tensor a (64) must match the size of tensor b (6) at non-singleton dimension 1"? | How can I resolve "RuntimeError: The size of tensor a (64) must match the size of tensor b (6) at non-singleton dimension 1"?
I am training a diffusion model for an image-to-image translation task. Image size is 128 by 128, and batch size is 8 (due to memory limitations).
This is the model I am using:
class ... | https://stackoverflow.com/questions/79429107/how-can-i-resolve-runtimeerror-the-size-of-tensor-a-64-must-match-the-size-o | python, machine-learning, deep-learning, stable-diffusion, image-translation | 1,739,256,498 |
se_51403712 | stackoverflow | MACHINE_LEARNING | Implementation of AlexNet in Keras on cifar-10 gives poor accuracy | Implementation of AlexNet in Keras on cifar-10 gives poor accuracy
I tried implementing AlexNet as explained in this video. Pardon me if I have implemented it wrong, this is the code for my implementation it in keras.
Edit : The cifar-10 ImageDataGenerator
cifar_generator = ImageDataGenerator()
cifar_data = cifar... | https://stackoverflow.com/questions/51403712/implementation-of-alexnet-in-keras-on-cifar-10-gives-poor-accuracy | machine-learning, keras, neural-network, deep-learning, conv-neural-network | 1,531,921,675 |
se_79437180 | stackoverflow | MACHINE_LEARNING | Tensorflow perfomance issue | Tensorflow perfomance issue
I'm trying to do a very primitive reinforced learning model on tensorflow. Although it's relatively small, a single iteration takes ~6-7 seconds.
def build_model():
model = keras.Sequential([
layers.Input(shape=(400,)),
layers.Dense(128, activation="relu"),
layer... | https://stackoverflow.com/questions/79437180/tensorflow-perfomance-issue | python, python-3.x, tensorflow, machine-learning | 1,739,466,429 |
se_79309001 | stackoverflow | MACHINE_LEARNING | Custom Labelling in Multi-Class Classification in XGBoost/ LightGBM | Custom Labelling in Multi-Class Classification in XGBoost/ LightGBM
I have the following dataframe which records the IQ, Hours (number of hours of studying) and Score (past exam score for student 1,2,3,4 in different classes (Class_ID) and I would like to use these features to predict who is going to graduate top of t... | https://stackoverflow.com/questions/79309001/custom-labelling-in-multi-class-classification-in-xgboost-lightgbm | machine-learning, xgboost, multiclass-classification, lightgbm, xgbclassifier | 1,735,201,095 |
se_71613305 | stackoverflow | MACHINE_LEARNING | How to process requests from multiiple users using ML model and FastAPI? | How to process requests from multiiple users using ML model and FastAPI?
I'm studying the process of distributing artificial intelligence modules through FastAPI.
I created a FastAPI app that answers questions using a pre-learned Machine Learning model.
In this case, it is not a problem for one user to use it, but whe... | https://stackoverflow.com/questions/71613305/how-to-process-requests-from-multiiple-users-using-ml-model-and-fastapi | python, machine-learning, multiprocessing, fastapi | 1,648,192,412 |
se_57978541 | stackoverflow | MACHINE_LEARNING | Xgboost Underfitting | Xgboost Underfitting
i trained the following Xgboost classifier :
xgb.XGBClassifier(tree_method='hist', grow_policy='lossguide',gamma=1.0, max_depth=0, max_leaves=255, min_child_weight=100,n_estimators=500,
n_jobs=-1,
learning_rate=0.1,
subsample=0.7,
... | https://stackoverflow.com/questions/57978541/xgboost-underfitting | python, machine-learning, xgboost | 1,568,738,163 |
se_65343377 | stackoverflow | MACHINE_LEARNING | Adam optimizer with warmup on PyTorch | Adam optimizer with warmup on PyTorch
In the paper Attention is all you need, under section 5.3, the authors suggested to increase the learning rate linearly and then decrease proportionally to the inverse square root of steps.
How do we implement this in PyTorch with Adam optimizer? Preferably without additional pac... | https://stackoverflow.com/questions/65343377/adam-optimizer-with-warmup-on-pytorch | python, machine-learning, pytorch | 1,608,217,976 |
se_71498324 | stackoverflow | MACHINE_LEARNING | Pytorch RuntimeError: CUDA out of memory with a huge amount of free memory | Pytorch RuntimeError: CUDA out of memory with a huge amount of free memory
While training the model, I encountered the following problem:
RuntimeError: CUDA out of memory. Tried to allocate 304.00 MiB (GPU 0; 8.00 GiB total capacity; 142.76 MiB already allocated; 6.32 GiB free; 158.00 MiB reserved in total by PyTorch)... | https://stackoverflow.com/questions/71498324/pytorch-runtimeerror-cuda-out-of-memory-with-a-huge-amount-of-free-memory | python, machine-learning, pytorch, computer-vision | 1,647,438,825 |
se_71193740 | stackoverflow | MACHINE_LEARNING | TypeError: Encoders require their input to be uniformly strings or numbers. Got ['int', 'str'] | TypeError: Encoders require their input to be uniformly strings or numbers. Got ['int', 'str']
I already referred the posts here, here and here. Don't mark it as duplicate.
I am working on a binary classification problem where my dataset has categorical and numerical columns.
However, some of the categ... | https://stackoverflow.com/questions/71193740/typeerror-encoders-require-their-input-to-be-uniformly-strings-or-numbers-got | python, pandas, machine-learning, scikit-learn, smote | 1,645,355,042 |
se_55332339 | stackoverflow | MACHINE_LEARNING | Error "could not convert string to float: 'INLAND'" | Error "could not convert string to float: 'INLAND'"
I'm doing a project on housing price prediction using machine learning, and want to submit it to a private firm for an application.
I am working in the Jupiter notebook for this project, but I am unable to fix the bugs regarding conversion for word... | https://stackoverflow.com/questions/55332339/error-could-not-convert-string-to-float-inland | python, machine-learning, scikit-learn | 1,553,495,639 |
se_79430043 | stackoverflow | MACHINE_LEARNING | XGBoost bst.predict() output not matching with manual calculation from the (text) tree model for binary:logistic case | XGBoost bst.predict() output not matching with manual calculation from the (text) tree model for binary:logistic case
I am trying to validate the XGBoost output (booster.predict) for logistic regression wrt my understanding of output calculation via the trees built. I see a difference of around -1.58 factor in all my ... | https://stackoverflow.com/questions/79430043/xgboost-bst-predict-output-not-matching-with-manual-calculation-from-the-text | python, machine-learning, xgboost, xgbclassifier | 1,739,278,507 |
se_79409149 | stackoverflow | MACHINE_LEARNING | Why do I have to unsqueeze the data from torch.Size([50]) to torch.Size([50, 1]) | Why do I have to unsqueeze the data from torch.Size([50]) to torch.Size([50, 1])
I was doing the PyTorch Deep Learning course from FreeCodeCamp and the doubt is:
weight = 0.7
bias = 0.3
start = 0
end = 1
step = 0.02
X = torch.arange(start, end, step).unsqueeze(dim=1)
y=weight*X + bias
X[:10], y[:10]
train_split=int(0... | https://stackoverflow.com/questions/79409149/why-do-i-have-to-unsqueeze-the-data-from-torch-size50-to-torch-size50-1 | python, machine-learning, deep-learning, pytorch | 1,738,593,848 |
se_61742408 | stackoverflow | MACHINE_LEARNING | Data Annotation for Machine Learning | Data Annotation for Machine Learning
I am going to develop a machine learning model. I have large data sets(Text). I need overall better accuracy F1 score etc. I am using data annotation tools(Dataturks). Which approach will be good to label the data as single label per entity or multiple label per entity (like there ... | https://stackoverflow.com/questions/61742408/data-annotation-for-machine-learning | machine-learning, nlp, data-annotations, spacy, named-entity-recognition | 1,589,248,043 |
se_57862633 | stackoverflow | MACHINE_LEARNING | Logistic regression curve not centered with my data | Logistic regression curve not centered with my data
I am doing a school project with logistic regression for binary classification and I am getting pretty bad results (accuracy around 50%). I had to do this classification from scratch so I am worried there is a problem with my implementation.
I fit a model with a sin... | https://stackoverflow.com/questions/57862633/logistic-regression-curve-not-centered-with-my-data | machine-learning, regression | 1,568,075,647 |
se_79422978 | stackoverflow | MACHINE_LEARNING | Different concate dimension parameters in the up-and-down sampling phase of U-shaped networks in the diffusion model | Different concate dimension parameters in the up-and-down sampling phase of U-shaped networks in the diffusion model
The error I am getting is
File "/media/xd/hdd/wxy/spectraldiff_diffusion-master/codes/unet3d.py", line 113, in forward
x = torch.cat((x, residual_x), dim=1)
RuntimeError: Sizes of tensors must ma... | https://stackoverflow.com/questions/79422978/different-concate-dimension-parameters-in-the-up-and-down-sampling-phase-of-u-sh | python, machine-learning, deep-learning, pytorch, neural-network | 1,739,009,674 |
se_25228219 | stackoverflow | MACHINE_LEARNING | Clustering of news articles | Clustering of news articles
My scenario is pretty straightforwrd: I have a bunch of news articles (~1k at the moment) for which I know that some cover the same story/topic. I now would like to group these articles based on shared story/topic, i.e., based on their similarity.
What I did so far is to apply basic NLP te... | https://stackoverflow.com/questions/25228219/clustering-of-news-articles | machine-learning, nlp, cluster-analysis, information-retrieval, unsupervised-learning | 1,407,670,745 |
se_79428265 | stackoverflow | MACHINE_LEARNING | Failed to execute a prediction with the Tensorflow C++ API | Failed to execute a prediction with the Tensorflow C++ API
I have created and trained a model to recognize some cartoon's character.
I'm using TensorFlow 2.18, and the model trained with TF Python API is accurate enough.
The accuracy is pretty excellent.
After the training, the model is saved with tensorflow.saved_mod... | https://stackoverflow.com/questions/79428265/failed-to-execute-a-prediction-with-the-tensorflow-c-api | c++, tensorflow, machine-learning | 1,739,220,246 |
se_45604143 | stackoverflow | MACHINE_LEARNING | Clustering time series data in Python | Clustering time series data in Python
I am trying to cluster time series data in Python using different clustering techniques. K-means didn't give good results. The following images are what I have after clustering using agglomerative clustering. I also tried Dynamic Time warping. These two seem to give similar result... | https://stackoverflow.com/questions/45604143/clustering-time-series-data-in-python | machine-learning, time-series, cluster-analysis, hierarchical-clustering | 1,502,337,060 |
se_35438540 | stackoverflow | MACHINE_LEARNING | Python Supervised Machine Learning | Python Supervised Machine Learning
I am trying to understand how to use scikit for supervised machine learning so I've made up some data belonging to two different sets: set A and set B. I have 18 elements in set A and 18 elements in set B. Each of the elements have three variables. See below:
#SetA
Variable1A = [ 3,... | https://stackoverflow.com/questions/35438540/python-supervised-machine-learning | python, machine-learning, supervised-learning | 1,455,641,988 |
se_45582182 | stackoverflow | MACHINE_LEARNING | Possibility of identification of non trained item in Machine Learning | Possibility of identification of non trained item in Machine Learning
A machine learning model has been trained to recognize the name of Animals and Plants. If suppose an automobile name is given, is it possible to say that the given name doesn't belong to the category animals or plants. If possible, kindly mention th... | https://stackoverflow.com/questions/45582182/possibility-of-identification-of-non-trained-item-in-machine-learning | machine-learning, deep-learning, neural-network, artificial-intelligence | 1,502,255,906 |
se_65645125 | stackoverflow | MACHINE_LEARNING | Producing a confusion matrix with cross_validate | Producing a confusion matrix with cross_validate
I'm trying to figure out how to produce a confusion matrix with cross_validate. I'm able to print out the scores with the code I have so far.
# Instantiating model
model = DecisionTreeClassifier()
#Scores
scoring = {'accuracy' : make_scorer(accuracy_score),
... | https://stackoverflow.com/questions/65645125/producing-a-confusion-matrix-with-cross-validate | python, machine-learning, scikit-learn, cross-validation, confusion-matrix | 1,610,210,788 |
se_9734403 | stackoverflow | MACHINE_LEARNING | Confusion matrix with cross validation | Confusion matrix with cross validation
I am training a svm classifier with cross validation (stratifiedKfold) using the scikits interfaces. For each test set (of k), I get a classification result. I want to have a confusion matrix with all the results.
Scikit-learn has a confusion matrix interface:
sklearn.metrics.con... | https://stackoverflow.com/questions/9734403/confusion-matrix-with-cross-validation | python, machine-learning, scikit-learn | 1,331,888,759 |
se_40169152 | stackoverflow | MACHINE_LEARNING | Confusion Matrix for 10-fold cross validation in scikit learn | Confusion Matrix for 10-fold cross validation in scikit learn
How can I calculate confusion matrix in 10-fold cross-validation with scikit-learn? How can I find y_test and y_pred? | https://stackoverflow.com/questions/40169152/confusion-matrix-for-10-fold-cross-validation-in-scikit-learn | python, machine-learning, scikit-learn, cross-validation, confusion-matrix | 1,477,028,370 |
se_79416292 | stackoverflow | MACHINE_LEARNING | Is there a way to set the data_min and the data_max in MinMaxScaler()? | Is there a way to set the data_min and the data_max in MinMaxScaler()?
I'm currently using MinMaxScaler() on my dataset. However, because my dataset is large I'm doing a first iteration pass in batches to compute the Min and Max Values for my Scaler. i'm using partial_fit() to help with this.
Anyway, for some of my fe... | https://stackoverflow.com/questions/79416292/is-there-a-way-to-set-the-data-min-and-the-data-max-in-minmaxscaler | machine-learning, scikit-learn, scaling, data-preprocessing | 1,738,792,655 |
se_72611335 | stackoverflow | MACHINE_LEARNING | What are the differences between fine tuning and few shot learning? | What are the differences between fine tuning and few shot learning?
I am trying to understand the concept of fine-tuning and few-shot learning.
I understand the need for fine-tuning. It is essentially tuning a pre-trained model to a specific downstream task. However, recently I have seen a plethora of blog posts stati... | https://stackoverflow.com/questions/72611335/what-are-the-differences-between-fine-tuning-and-few-shot-learning | machine-learning, deep-learning, artificial-intelligence, fine-tuning, few-shot-learning | 1,655,178,863 |
se_79411501 | stackoverflow | MACHINE_LEARNING | How to pass Input to a tensorflow backbone model without getting AttributeError: 'tuple' object has no attribute 'as_list' | How to pass Input to a tensorflow backbone model without getting AttributeError: 'tuple' object has no attribute 'as_list'
I am trying to use ResNet3D from tensorflow-models library but I am getting this weird error when trying to run the block
!pip install tf-models-official==2.17.0
Tensorflow versio... | https://stackoverflow.com/questions/79411501/how-to-pass-input-to-a-tensorflow-backbone-model-without-getting-attributeerror | python, tensorflow, machine-learning, deep-learning, tf.keras | 1,738,668,161 |
se_79388942 | stackoverflow | MACHINE_LEARNING | Using SavedModel format in Keras 3.5 | Using SavedModel format in Keras 3.5
I came up against a problem when trying to use tf.keras.models.load_model(Path_to_pb_model) to load a Savedformat model.
I'm using Tensorflow 2.17.1 with Keras 3.5.
Apparently Keras 3 only accepts .keras or .h5 formats.
First off, I'm a bit confused because according to this docume... | https://stackoverflow.com/questions/79388942/using-savedmodel-format-in-keras-3-5 | machine-learning, keras, tensorflow2.0, tf.keras | 1,737,911,174 |
se_3495157 | stackoverflow | MACHINE_LEARNING | Ordinal classification packages and algorithms | Ordinal classification packages and algorithms
I'm attempting to make a classifier that chooses a rating (1-5) for a item i. For each item i, I have a vector x containing about 40 different quantities pertaining to i. I also have a gold standard rating for each item. Based on some function of x, I want to train a c... | https://stackoverflow.com/questions/3495157/ordinal-classification-packages-and-algorithms | machine-learning, classification | 1,281,975,953 |
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