I have a data set with huge number of features ( Approximately 3000) and a binary target variable . The reason I have too many features is because of one hot encoding many categorical variables in my data set .
I think logistic regression might only work with small number of features .
So , given that I have many features , which algorithm should I use for better classification score ?
My aim is to increase the ROC-AUC metric for this classification task .
Is it better to use SVM or Neural networks ?