What are the recommended over-sampling or under-sampling techniques to handle multi-class imbalanced datasets for machine learning?
8922
Opinions about Oversampling in general, and the SMOTE algorithm in particular
150758
How does cross-validation overcome the overfitting problem?
32234
Reference for random forests
59364
Why should the data be shuffled for machine learning tasks
156676
How to compare features and classifiers which achieve perfect accuracy?
17834
Calculating the optimal number of bins for severely skewed data
48226
How to adjust the hyperparameters of MLP classifier to get more perfect performance
34133
Mann-Whitney-Wilcoxon Test on highly unbalanced groups.
122165
What problem does oversampling, undersampling, and SMOTE solve?
31300
Does an unbalanced sample matter when doing logistic regression?
42256
Binary classification with strongly unbalanced classes
113807
Testing Classification on Oversampled Imbalance Data
141640
Sklearn - Choosing the right model for supervised learning/classification task
6024
How to deal with hierarchical / nested data in machine learning
104438
Random Forest mtry Spit-to-Split Variable Sampling Procedure
16895
"User memory limit exceeded" using Random Forest classification
10321
How can I pool bootstrapped p-values across multiply imputed data sets?