This project is designed to help rapidly apply a standard machine learning analysis to a new data set.

I want to run logistic regression, random forests, and neural nets on my dataset. i want to scale the features.

python analyze.py path/to/dataset -ml LogisticRegression,RandomForestClassifier,MLPClassifier -prep RobustScaler 

I want to tune the parameters of each method using 100 combinations, and run 10 shuffles of the data.

python analyze.py path/to/dataset -ml LogisticRegression,RandomForestClassifier,MLPClassifier -prep RobustScaler -n_combos 100 -n_trials 10

what other options are there?

python analyze.py -h

python compare.py path/to/results