python - % in pandas invalid literal for float(): -


i tried running random forest model on loan data set, loaded csv file pandas dataframe, , used variable loan_amnt,int_rate feature, loan_status_b 1 or 0 label.

my dataframe looks this:

my dataframe looks this

traning_set = train[['loan_amnt','int_rate','loan_status_b']] features_train = array(traning_set[['loan_amnt','int_rate']]) labels_train = array(traning_set[['loan_status_b']])

i created test set in same way

#random forest sklearn.ensemble import randomforestclassifier clf = randomforestclassifier(n_estimators=10) clf = clf.fit(features_train, labels_train)  pred = clf.predict(features_test)  sklearn.metrics import accuracy_score print accuracy_score(labels_test, pred)

this produced valueerror: invalid literal float(): 19.20% has encountered problem before or knows how fix it? thank you!


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