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from cuml.model_selection import train_test_split

from cuml.model_selection import train_test_split

from sklearn.model_selection import cross_val_score,train_test_split

import cudf as pd

import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

data = pd.read_csv('../input/voicegender/voice.csv')

data.isnull().sum()

data.shape

new_data = data.drop(['sfm', 'kurt', 'meandom', 'meanfreq', 'dfrange', 'modindx'], axis=1)
new_data

new_data['label'] = new_data['label'].map({'male': 1, 'female': 0})
print(new_data)
from cuml.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(new_data.iloc[:, :-1].values, new_data.iloc[:, -1].values, test_size=0.2, random_state=42)