PythonForDataScience/makeSubmission.py at master · techinAI/PythonForDataScience · GitHub

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import pandas as pd

from sklearn.ensemble import RandomForestClassifier

def main():

# create the training & test sets

dataset = pd.read_csv('Data/train.csv')

target = dataset.Activity.values

train = dataset.drop('Activity', axis=1).values

test = pd.read_csv('Data/test.csv').values

# create and train the random forest

# n_jobs set to -1 will use the number of cores present on your system.

rf = RandomForestClassifier(n_estimators=100, n_jobs=-1)

rf.fit(train, target)

predicted_probs = [x[1] for x in rf.predict_proba(test)]

predicted_probs = pd.Series(predicted_probs)

predicted_probs.to_csv('Data/submission.csv', index=False,

float_format="%f")

if __name__ == "__main__":

main()