How to Deal with Large Number of Dummy Variables in Machine Learning?
10256
Principled way of collapsing categorical variables with many levels?
34949
Generating a high-dimensional dataset where nearest neighbor becomes meaningless
101622
Choosing number of principal components to retain
148679
Modelling with more variables than data points
11188
Can principal component analysis be applied to datasets containing a mix of continuous and categorical variables?
37433
How to build a predictive model when more levels of a categorical predictor are possible than appear in the training data
106186
How to analyze data with more than one associated categorical dependent variables?
126595
Does feature selection help improve the performance of machine learning?
143441
Getting Warning: " 'newdata' had 1 row but variables found have 32 rows" on predict.lm
49848
Label encoding vs Dummy variable/one hot encoding - correctness?
151342
Is there an optimal loss function for dealing with imbalanced classes?
48892
whether to rescale indicator / binary / dummy predictors for LASSO
131146
Create an adaptive amount of local variables for error propagation
53821
interpretation of dummy coded linear regression
66215
Training a decision tree against unbalanced data
132484
Not so easy optimization of variables?
34324
How would you deal with a bimodally distributed predictor variable in bivariate logistic regression?