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Category:Video game downloadable content Category:Video games with cross-platform play Category:Nippon Ichi Software games Category:Xbox One games Category:Video games developed in Japan Category:Windows games Category:Windows-only games Category:Upcoming video gamesQ: TypeError: only int or long objects are allowed to convert or shift I am trying to use the random sample technique in scikit-learn for the cross-validation and I get this error: TypeError: only int or long objects are allowed to convert or shift I tried to use the numpy module but I still get the same error. I am using Python 3.5.2, Scipy 1.1.0, numpy 1.13.1 from sklearn.model_selection import StratifiedKFold from sklearn.ensemble import RandomForestClassifier from sklearn.pipeline import make_pipeline from sklearn.datasets import load_iris from sklearn.model_selection import cross_val_score from sklearn.feature_extraction.text import TfidfTransformer from sklearn.feature_extraction.text import CountVectorizer import numpy as np import matplotlib.pyplot as plt iris = load_iris() X, y = iris.data, iris.target X_train, X_test, y_train, y_test = X[:100], X[100:160], y[:100], y[100:] X_train = np.array(X_train) X_test = np.array(X_test) y_train = np.array(y_train) y_test = np.array(y_test) X_train = X_train.astype('float32') X_test = X_test.astype('float32') X_train /= 255 X_test /= 255 rf = RandomForestClassifier(random_state=1234) tfidf = TfidfTransformer() cv = CountVectorizer(binary=False) pipeline = make_pipeline(tfidf, cv) y_train = np.array

 

 

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