Should one scale the full dataset or the training set directly
8703
How to apply standardization/normalization to train- and testset if prediction is the goal?
112380
Why should boostrap sample size equal the original sample size?
141640
Sklearn - Choosing the right model for supervised learning/classification task
142784
For linear classifiers, do larger coefficients imply more important features?
112991
What algorithms need feature scaling, beside from SVM?
38075
What is the trade-off between batch size and number of iterations to train a neural network?
82881
How to do data augmentation and train-validate split?
145996
Difference between scaling horizontally and vertically for databases
22203
Data normalization and standardization in neural networks
10855
How to use early stopping properly for training deep neural network?
152239
Dataset collapsing/reducing
108282
How to choose between learning algorithms
145721
What is the exact purpose of object scale?
146238
How to deal with a data-set having all the samples with every feature-point almost similar?
138454
Determining sample size for ML algorithm validation
59364
Why should the data be shuffled for machine learning tasks
58047
Decision Trees and Regression - Can predicted values be outside range of training data?