# 4 Class Classification - Machine Learning Model

I have a data set which contains nearly 150 features and 60k data. And my target feature is continuous variable represents hours. I divided this period into 4 categories of user engagement (4 ranges of hours). Implement GA with SVM, GA with logistic regression, Random forest, GA with KNN with suitable normalization of data wherever required. Used GA for best feature subset selection.

All the algorithms gave similar results of around 46% accuracy ( for nearly balanced test set).

Note: Training is also done on a balanced data set. I am wondering where am I gone wrong?

I believe I went wrong somewhere in input to target mapping. Could anyone please confirm that categorization of the continuous target variable (hrs) into 4 sets are reasonable?