{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Cross Validation with KFold"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 試著print出X_train, X_test，並將shuffle改成True看看結果如何變化。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import KFold\n",
    "X = np.array([[1, 2], [3, 4], [5, 6], [7, 8], [9, 10]])\n",
    "y = np.array([1, 2, 3, 4, 5])\n",
    "kf = KFold(n_splits=5, random_state=None, shuffle=False)\n",
    "for train_index, val_index in kf.split(X):\n",
    "    X_train, X_val = X[train_index], X[val_index]\n",
    "    y_train, y_val = y[train_index], y[val_index]\n",
    "    print(\"TRAIN index:\", train_index, \"Validation index:\", val_index)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Print Training and Validation data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "i = 1\n",
    "for train_index, val_index in kf.split(X):\n",
    "    X_train, X_val = X[train_index], X[val_index]\n",
    "    y_train, y_val = y[train_index], y[val_index]\n",
    "    print('Cross Validation%d==============' % i, '\\n'\n",
    "          \"TRAIN data:\", '\\n', X_train, '\\n', \"Validation data:\", X_val)\n",
    "    i += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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