Random Indices for train and test

randPartition.py

import numpy as np
import random


def randPartition(alldata_X, alldata_Y, _FRACTION):
    """
    alldata_X : All of your X (Features) data
    alldata_Y : All of your Y (Prediction) data
    _FRACTION : The fraction of data rows you want for train (0.75 means you need 75% of your data as train and 25% as test)
    """
    np.random.seed(0)
    indices = np.arange(alldata_X.shape[0])
    np.random.shuffle(indices)

    dataX = alldata_X[indices]
    dataY = alldata_Y[indices]

    partition_index = int(dataX.shape[0] * _FRACTION)

    trainX = dataX[0:partition_index]
    testX = dataX[partition_index:dataX.shape[0]]

    trainY = dataY[0:partition_index]
    testY = dataY[partition_index:dataY.shape[0]]

    return [trainX, trainY, testX, testY]