A technique in cross-validation where the data is partitioned into k subsets (or "folds"), where the first k-1 folds are used for training and the last fold for evaluation. The process is repeated k times, leaving out a different fold for evaluation each time.
Questions tagged [k-fold]
284 questions
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Splitting a list of folds into training and validation sets
I have created code that splits data into folds (7 in this case). In effect, I have a list of lists of 7 folds of data.
I now want to go through these and split into training and validation sets within each fold and store these as data frames.
As a…
DWS
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Using Kfold for cross validation
I am using the following code for 5 fold cross validation. I am getting error as kfold is not iterable. I have tried to use shuffle, writing number of folds different way but still getting error.
from sklearn.model_selection import…
Ananya Chakraborty
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If not chosen all the data in the train partition, is it still k-fold cross validation?
I have a dataset of 900 images, distributed across 6 classes, with 150 images per class. To develop a classifier and assess its performance, I will utilize k-fold cross-validation. In this case, I will employ 3-fold cross-validation.
For each fold,…
noone
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StratifiedKFold called from multiprocessing loop gives same results for each process
I'm writing a custom GridSearchCV function by calling StratifiedKFold from my multiprocess loop
StratifiedKFold is giving the same accuracy n times, n = number of processes
import multiprocessing
PROCESSES = 5
with multiprocessing.Pool(PROCESSES)…
sam
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Print classification result with k fold classification with sklearn package
I have a dataset that I spilt by the holdout method using sklearn. The following is the procedure
from sklearn.model_selection import train_test_split
(X_train, X_test, y_train, y_test)=train_test_split(X,y,test_size=0.3, stratify=y)
I am using…
Encipher
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Neural network regression: the Difference between training MAE and cross-validation results
I'm working on a regression task using a neural network implemented in Keras. I trained the model for 1000 epochs, and on the last epoch, I obtained a mean absolute error (MAE) value of 3.8 However, when I performed cross-validation using…
Salah Amani
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How to use cross_cal_score for MNIST dataset? How to fix: "ValueError: Shapes (None, 1) and (None, 10) are incompatible"
How to use cross_cal_score for MNIST dataset? Shapes between the output of my model and the y in cross_cal_score are incompatible.
I would like to perform k-fold cross validation for MNIST dataset (an example in DEEP LEARNING: FROM BASICS TO…
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How to save history for k-fold cross-validation Tensorflow model?
I have a Tensorflow workflow set-up to split my training data and use k-fold cross-validation where the script iterates k-times and trains a new model on each subset of the data. However, I'm having an issue saving the individual training history…
Phil Wernette
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How to use K-Fold cross validation with DenseNet121 model
I am working on classification of images breast cancer using DensetNet121 pretrained model. I split the dataset into training, testing and validation. I want to apply k-fold cross validation. I used cross_validation from sklearn library, but I get…
Eda
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K-fold to train a machine learning model
I have a big question today for which I can't figure out the real solution. I make a stratified K-folding to my gridsearch (to search the good hyperparameter for my ML model).
Can I take the best fold for training my final model. For example, there…
Romain LOMBARDI
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Large differences in accuracy between different folds in kFold validation
I am using the VGG16 model on spectrograms without any pre-training. I am currently doing KFold validation but while in one the accuracy reaches 99%, in another one it stays at 53%.
Can anyone help me with it? Why and how to solve it?
On the fold…
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What is the purpose of using get_n_splits instead of an integer value?
n_folds = 5
def rmsle(model):
kf = KFold(n_folds, shuffle=True, random_state=42).get_n_splits(train.values)
rmse = np.sqrt(-cross_val_score(model, train.values, y_train, scoring="neg_mean_squared_error", cv = kf))
return(rmse)
I'm new…
황해준
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Python Validation/Test in K-fold when feeding into Neural Networks
I am using tensorflow neural network to predict on the whole dataset using K-fold method.
https://www.tensorflow.org/tutorials/structured_data/feature_columns
train, test = train_test_split(dataframe, test_size=0.2)
train, val =…
Armsinrius
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Equivalence of cv.glmnet for quantile regression R
Does any one know how to do K fold cross validation (with lasso penalty) for quantile regression including the weight of variables ? I found rqPen but it doesn't take account weight of variables.
Linear regression : cv.glmnet(X,Y lambda=...,…
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k-fold Cross-validation in segmention by cnn
I wrote a code for the segmentation of iris images and got relatively good results. But I need to do it better. I want to use k-fold cross validation.
I wrote a code for the segmentation of iris images and got relatively good results. But I need to…
mohammad zeidi
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