Hi,
I am trying to use random forest for my dataset that includes string values
also. The dataset that i used for training is a csv file but includes some
string categorical values also.
I had read the scikit preprocessing issues and it seems i shoudl have used
DictVectoricer to encode my categorical string values after i put them in a
dict format. But i am not sure how i will use the resulting output at the
random forest code.
Here is what i do basically fro random forest:
def main():
#read in the training file
train = csv_io.read_data("train.csv")
#set the training responses
target = [x[0] for x in train]
#set the training features
train = [x[1:] for x in train]
#read in the test file
realtest = csv_io.read_data("test.csv")
# random forest code
rf = RandomForestClassifier(n_estimators=150, min_samples_split=2,
n_jobs=-1)
# fit the training data
print('fitting the model')
rf.fit(train, target)
# run model against test data
predicted_probs = rf.predict_proba(realtest)
predicted_probs = ["%f" % x[1] for x in predicted_probs]
csv_io.write_delimited_file("random_forest_solution.csv",
predicted_probs)
print ('Random Forest Complete! You Rock! Submit
random_forest_solution.csv to Kaggle')
if __name__=="__main__":
main()
Will be happy if someone helps
--
Oğuz Yarımtepe
http://about.me/oguzy
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