andiac/cross_validation_std.ipynb

## cross_validation_std.ipynb
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7fec51257358>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "from scipy.stats import norm\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "true_samples = np.random.normal(0, 1, 9000)\n",
    "false_samples = np.random.normal(10, 1, 1000)\n",
    "false2_samples = np.random.normal(-20, 1, 1000)\n",
    "\n",
    "plt.scatter(true_samples, [0]*true_samples.shape[0])\n",
    "plt.scatter(false_samples, [0]*false_samples.shape[0])\n",
    "plt.scatter(false2_samples, [0]*false2_samples.shape[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([  5.,  23.,  79., 179., 236., 217., 165.,  72.,  21.,   3.]),\n",
       " array([-23.06158698, -22.43319577, -21.80480456, -21.17641335,\n",
       "        -20.54802214, -19.91963092, -19.29123971, -18.6628485 ,\n",
       "        -18.03445729, -17.40606607, -16.77767486]),\n",
       " <a list of 10 Patch objects>)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(true_samples)\n",
    "plt.hist(false_samples)\n",
    "plt.hist(false2_samples)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 697.,  303.,    0.,    0.,    0.,  920., 8004.,   76.,  355.,\n",
       "         645.]), array([-23.06158698, -19.42808195, -15.79457692, -12.16107189,\n",
       "         -8.52756686,  -4.89406182,  -1.26055679,   2.37294824,\n",
       "          6.00645327,   9.63995831,  13.27346334]), <a list of 10 Patch objects>)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "samples = np.concatenate((true_samples, false_samples, false2_samples))\n",
    "plt.hist(samples)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "res = [[] for i in range(11000)]\n",
    "\n",
    "for i, sample in enumerate(samples):\n",
    "    leave_i_out = np.concatenate((samples[0:i], samples[i+1:]))\n",
    "    assert leave_i_out.shape[0] == 10999\n",
    "    pred = np.mean(leave_i_out)\n",
    "    for j in range(i):\n",
    "        res[j].append(pred)\n",
    "    for j in range(i+1, 11000):\n",
    "        res[j].append(pred)\n",
    "        \n",
    "for r in res:\n",
    "    assert len(r) == 10999"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([  3.,  17.,  52., 135., 196., 253., 199., 105.,  35.,   5.]),\n",
       " array([0.00061306, 0.00061308, 0.00061309, 0.0006131 , 0.00061312,\n",
       "        0.00061313, 0.00061315, 0.00061316, 0.00061318, 0.00061319,\n",
       "        0.00061321]),\n",
       " <a list of 10 Patch objects>)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "stds = []\n",
    "for r in res:\n",
    "    stds.append(np.std(r))\n",
    "plt.hist(stds[:9000])\n",
    "plt.hist(stds[9000:10000])\n",
    "plt.hist(stds[10000:11000])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}