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Discografiagrupoyaguarumediafire [2022-Latest]




I created the code in the jupyter notebook and tested it locally. Then I uploaded it to Kaggle and tested it with a simulated dataset to ensure it worked. My code is below, based on this example. %pylab inline import numpy as np import random x_train, x_test, y_train, y_test = random.load('Exported Data', return_X_y = False) x_train = x_train.astype('float32') x_test = x_test.astype('float32') x_train = x_train.reshape((x_train.shape[0], 1)) x_test = x_test.reshape((x_test.shape[0], 1)) y_train = np.zeros(len(x_train)) y_test = np.zeros(len(x_test)) for i in range(0, len(x_train)): y_train[i] = x_train[i] for i in range(0, len(x_test)): y_test[i] = x_test[i] import pandas as pd df = pd.DataFrame(x_train) df['y'] = y_train df = df.drop(['y'], axis=1) cols = ['x_train', 'y_train', 'x_test', 'y_test'] df = df.drop(['x_train', 'x_test', 'y_train', 'y_test'], axis=1) from sklearn.tree import DecisionTreeClassifier clf = DecisionTreeClassifier(), df['y'].reshape(-1, 1)) pred = clf.predict(df) print(pred) When I test it in Kaggle, I get the following error: ValueError: X has more columns than samples: 150 columns vs. 25 Any suggestions on how to resolve this? A: There is a bug with the Kaggle notebook in 0.6.0. I




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Discografiagrupoyaguarumediafire [2022-Latest]

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