【PYTHON】Mean Estimated Accuracy Naive Bayes

 from pandas import read_csv

from sklearn.model_selection import KFold from sklearn.model_selection import cross_val_score from sklearn.naive_bayes import GaussianNB filename = 'pima-indians-diabetes.csv' names = ['preg', 'plas', 'pres', 'skin', 'test', 'mass', 'pedi', 'age', 'class'] dataframe = read_csv(filename, names=names) array = dataframe.values #splitting the array to input and output X = array[:,0:8] Y = array[:,8] num_folds = 10 seed = 7 kfold = KFold(n_splits = num_folds, random_state = seed) model = GaussianNB() results = cross_val_score(model, X, Y, cv=kfold) print("Mean Estimated Accuracy Naive Bayes: %f " % (results.mean()))

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