Is there a need to standardise training and test sets separately for binary classification problems?
6454
Perform feature normalization before or within model validation?
67179
AUC and class imbalance in training/test dataset
155013
How to validate k-fold cross validation results for classifiers?
96296
Imputation before or after splitting into train and test?
112991
What algorithms need feature scaling, beside from SVM?
13657
Cross Validation Vs Train Validation Test
21979
Feature selection for "final" model when performing cross-validation in machine learning
36290
Can the 'bin size' in a histogram be thought of as a regularity constraint?
120166
How to correctly use validation and test sets for Neural Network training?
54989
Why is binary cross entropy (or log loss) used in autoencoders for non-binary data
92956
Is it possible to train a neural network without backpropagation?
115455
What is the correct way to use train, validation and test set when comparing classifiers?
121682
Standardize Training and Validation Data
47570
Will decision trees perform splitting of nodes by converting categorical values to numerical in practice?
84469
Is there a thumb-rule for designing neural-networks?
89330
Machine Learning - Where is the difference between one-class, binary-class and multinominal-class classification?
83655
Assumptions behind cross-validation