NameError: name 'cross_val_score' is not defined

Code

import pandas as pd import numpy as np from sklearn.tree import DecisionTreeClassifier clf = DecisionTreeClassifier(random_state=14)

dataset = pd.read_csv("info.csv", parse_dates=[0], skiprows=[0, ]) # print (dataset) dataset.columns = ["Visitor Team", "VisitorPts", "Home Team", "HomePts"]

dataset.ix[:5]

dataset["HomeWin"] = dataset["VisitorPts"] < dataset["HomePts"] y_true = dataset["HomeWin"].values

from collections import defaultdict

won_last = defaultdict(int)

dict_variable = {}

for index, row in dataset.iterrows(): # remove two print lines below if you don't need them # I have included them to show the output on terminal #print index #print row home_team = row["Home Team"] visitor_team = row["Visitor Team"] row["HomeLastWin"] = won_last[home_team] row["VisitorLastWin"] = won_last[visitor_team] dataset.ix[index] = row won_last[home_team] = row["HomeWin"] won_last[visitor_team] = not row["HomeWin"]

from collections import defaultdict won_last = defaultdict(int)

for index, row in dataset.iterrows(): home_team = row["Home Team"] visitor_team = row["Visitor Team"] row["HomeLastWin"] = won_last[home_team] row["VisitorLastWin"] = won_last[visitor_team] dataset.ix[index] = row won_last[home_team] = row["HomeWin"] won_last[visitor_team] = not row["HomeWin"] X_previouswins = dataset[["HomeLastWin", "VisitorLastWin"]].values

scores = cross_val_score(clf, X_previouswins, y_true, scoring='accuracy') print("Accuracy: {0:.1f}%".format(np.mean(scores) * 100))