basic_classify.py

import competition_utilities as cu
import basic_features as features
from sklearn.ensemble import RandomForestClassifier

train_file = "train-A.csv"
full_train_file = "train.csv"
test_file = "public_leaderboard.csv"
submission_file = "basic_classify_v2.csv"

feature_names = [ "BodyLength"
                , "NumTags"
                , "OwnerUndeletedAnswerCountAtPostTime"
                , "ReputationAtPostCreation"
                , "TitleLength"
                , "TitleWordCount"
                , "UserAge"
                ]

def main():
    print("Reading the data")
    data = cu.get_dataframe(train_file)

    print("Extracting features")
    fea = features.extract_features(feature_names, data)

    print("Training the model")
    rf = RandomForestClassifier(n_estimators=60, verbose=2, compute_importances=True, n_jobs=-1)
    rf.fit(fea, data["OpenStatus"])

    print("Reading test file and making predictions")
    data = cu.get_dataframe(test_file)
    test_features = features.extract_features(feature_names, data)
    probs = rf.predict_proba(test_features)

    print("Calculating priors and updating posteriors")
    new_priors = cu.get_priors(full_train_file)
    old_priors = cu.get_priors(train_file)
    probs = cu.cap_and_update_priors(old_priors, probs, new_priors, 0.001)
    
    print("Saving submission to %s" % submission_file)
    cu.write_submission(submission_file, probs)

if __name__=="__main__":
    main()