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Smaple Random Forest
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from sklearn.ensemble import RandomForestClassifier | |
from numpy import genfromtxt, savetxt | |
def main(): | |
#create the training & test sets, skipping the header row with [1:] | |
dataset = genfromtxt(open('Data/train.csv','r'), delimiter=',', dtype='f8')[1:] | |
target = [x[0] for x in dataset] | |
train = [x[1:] for x in dataset] | |
test = genfromtxt(open('Data/test.csv','r'), delimiter=',', dtype='f8')[1:] | |
#create and train the random forest | |
#multi-core CPUs can use: rf = RandomForestClassifier(n_estimators=100, n_jobs=2) | |
rf = RandomForestClassifier(n_estimators=100) | |
rf.fit(train, target) | |
savetxt('Data/submission2.csv', rf.predict(test), delimiter=',', fmt='%f') | |
if __name__=="__main__": | |
main() |
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