ML_lab07.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: tensorflow in c:\\users\\tasha\\anaconda3\\lib\\site-packages (2.3.1)\n",
      "Requirement already satisfied: gast==0.3.3 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from tensorflow) (0.3.3)\n",
      "Requirement already satisfied: tensorboard<3,>=2.3.0 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from tensorflow) (2.3.0)\n",
      "Requirement already satisfied: h5py<2.11.0,>=2.10.0 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from tensorflow) (2.10.0)\n",
      "Requirement already satisfied: protobuf>=3.9.2 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from tensorflow) (3.13.0)\n",
      "Requirement already satisfied: keras-preprocessing<1.2,>=1.1.1 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from tensorflow) (1.1.2)\n",
      "Requirement already satisfied: wrapt>=1.11.1 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from tensorflow) (1.11.2)\n",
      "Requirement already satisfied: wheel>=0.26 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from tensorflow) (0.34.2)\n",
      "Requirement already satisfied: grpcio>=1.8.6 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from tensorflow) (1.32.0)\n",
      "Requirement already satisfied: absl-py>=0.7.0 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from tensorflow) (0.10.0)\n",
      "Requirement already satisfied: tensorflow-estimator<2.4.0,>=2.3.0 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from tensorflow) (2.3.0)\n",
      "Requirement already satisfied: opt-einsum>=2.3.2 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from tensorflow) (3.3.0)\n",
      "Requirement already satisfied: google-pasta>=0.1.8 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from tensorflow) (0.2.0)\n",
      "Requirement already satisfied: astunparse==1.6.3 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from tensorflow) (1.6.3)\n",
      "Requirement already satisfied: six>=1.12.0 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from tensorflow) (1.15.0)\n",
      "Requirement already satisfied: numpy<1.19.0,>=1.16.0 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from tensorflow) (1.18.5)\n",
      "Requirement already satisfied: termcolor>=1.1.0 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from tensorflow) (1.1.0)\n",
      "Requirement already satisfied: markdown>=2.6.8 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from tensorboard<3,>=2.3.0->tensorflow) (3.2.2)\n",
      "Requirement already satisfied: google-auth-oauthlib<0.5,>=0.4.1 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from tensorboard<3,>=2.3.0->tensorflow) (0.4.1)\n",
      "Requirement already satisfied: requests<3,>=2.21.0 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from tensorboard<3,>=2.3.0->tensorflow) (2.24.0)\n",
      "Requirement already satisfied: setuptools>=41.0.0 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from tensorboard<3,>=2.3.0->tensorflow) (49.2.0.post20200714)\n",
      "Requirement already satisfied: tensorboard-plugin-wit>=1.6.0 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from tensorboard<3,>=2.3.0->tensorflow) (1.7.0)\n",
      "Requirement already satisfied: google-auth<2,>=1.6.3 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from tensorboard<3,>=2.3.0->tensorflow) (1.22.0)\n",
      "Requirement already satisfied: werkzeug>=0.11.15 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from tensorboard<3,>=2.3.0->tensorflow) (1.0.1)\n",
      "Requirement already satisfied: requests-oauthlib>=0.7.0 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from google-auth-oauthlib<0.5,>=0.4.1->tensorboard<3,>=2.3.0->tensorflow) (1.3.0)\n",
      "Requirement already satisfied: chardet<4,>=3.0.2 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard<3,>=2.3.0->tensorflow) (3.0.4)\n",
      "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard<3,>=2.3.0->tensorflow) (1.25.9)\n",
      "Requirement already satisfied: idna<3,>=2.5 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard<3,>=2.3.0->tensorflow) (2.10)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard<3,>=2.3.0->tensorflow) (2020.6.20)\n",
      "Requirement already satisfied: rsa<5,>=3.1.4; python_version >= \"3.5\" in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from google-auth<2,>=1.6.3->tensorboard<3,>=2.3.0->tensorflow) (4.6)\n",
      "Requirement already satisfied: pyasn1-modules>=0.2.1 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from google-auth<2,>=1.6.3->tensorboard<3,>=2.3.0->tensorflow) (0.2.8)\n",
      "Requirement already satisfied: aiohttp<4.0.0dev,>=3.6.2; python_version >= \"3.6\" in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from google-auth<2,>=1.6.3->tensorboard<3,>=2.3.0->tensorflow) (3.6.2)\n",
      "Requirement already satisfied: cachetools<5.0,>=2.0.0 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from google-auth<2,>=1.6.3->tensorboard<3,>=2.3.0->tensorflow) (4.1.1)\n",
      "Requirement already satisfied: oauthlib>=3.0.0 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tensorboard<3,>=2.3.0->tensorflow) (3.1.0)\n",
      "Requirement already satisfied: pyasn1>=0.1.3 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from rsa<5,>=3.1.4; python_version >= \"3.5\"->google-auth<2,>=1.6.3->tensorboard<3,>=2.3.0->tensorflow) (0.4.8)\n",
      "Requirement already satisfied: async-timeout<4.0,>=3.0 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from aiohttp<4.0.0dev,>=3.6.2; python_version >= \"3.6\"->google-auth<2,>=1.6.3->tensorboard<3,>=2.3.0->tensorflow) (3.0.1)\n",
      "Requirement already satisfied: multidict<5.0,>=4.5 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from aiohttp<4.0.0dev,>=3.6.2; python_version >= \"3.6\"->google-auth<2,>=1.6.3->tensorboard<3,>=2.3.0->tensorflow) (4.7.6)\n",
      "Requirement already satisfied: attrs>=17.3.0 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from aiohttp<4.0.0dev,>=3.6.2; python_version >= \"3.6\"->google-auth<2,>=1.6.3->tensorboard<3,>=2.3.0->tensorflow) (19.3.0)\n",
      "Requirement already satisfied: yarl<2.0,>=1.0 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from aiohttp<4.0.0dev,>=3.6.2; python_version >= \"3.6\"->google-auth<2,>=1.6.3->tensorboard<3,>=2.3.0->tensorflow) (1.6.0)\n",
      "Collecting keras\n",
      "  Downloading Keras-2.4.3-py2.py3-none-any.whl (36 kB)\n",
      "Requirement already satisfied: scipy>=0.14 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from keras) (1.5.0)\n",
      "Requirement already satisfied: h5py in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from keras) (2.10.0)\n",
      "Requirement already satisfied: pyyaml in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from keras) (5.3.1)\n",
      "Requirement already satisfied: numpy>=1.9.1 in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from keras) (1.18.5)\n",
      "Requirement already satisfied: six in c:\\users\\tasha\\anaconda3\\lib\\site-packages (from h5py->keras) (1.15.0)\n",
      "Installing collected packages: keras\n",
      "Successfully installed keras-2.4.3\n"
     ]
    }
   ],
   "source": [
    "!pip install tensorflow\n",
    "!pip install keras"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential_5\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "dense_5 (Dense)              (None, 3)                 12        \n",
      "_________________________________________________________________\n",
      "activation_5 (Activation)    (None, 3)                 0         \n",
      "=================================================================\n",
      "Total params: 12\n",
      "Trainable params: 12\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n",
      "Epoch 1/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 5.0754 - accuracy: 0.3750\n",
      "Epoch 2/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 3.0065 - accuracy: 0.3750\n",
      "Epoch 3/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 1.3795 - accuracy: 0.3750\n",
      "Epoch 4/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1.2352 - accuracy: 0.2500\n",
      "Epoch 5/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 1.1811 - accuracy: 0.2500\n",
      "Epoch 6/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 1.1366 - accuracy: 0.2500\n",
      "Epoch 7/200\n",
      "1/1 [==============================] - 0s 5ms/step - loss: 1.1115 - accuracy: 0.2500\n",
      "Epoch 8/200\n",
      "1/1 [==============================] - 0s 5ms/step - loss: 1.0905 - accuracy: 0.2500\n",
      "Epoch 9/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1.0746 - accuracy: 0.2500\n",
      "Epoch 10/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1.0600 - accuracy: 0.2500\n",
      "Epoch 11/200\n",
      "1/1 [==============================] - 0s 5ms/step - loss: 1.0472 - accuracy: 0.2500\n",
      "Epoch 12/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 1.0351 - accuracy: 0.2500\n",
      "Epoch 13/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1.0240 - accuracy: 0.3750\n",
      "Epoch 14/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 1.0134 - accuracy: 0.5000\n",
      "Epoch 15/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 1.0034 - accuracy: 0.3750\n",
      "Epoch 16/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.9939 - accuracy: 0.2500\n",
      "Epoch 17/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.9848 - accuracy: 0.3750\n",
      "Epoch 18/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.9761 - accuracy: 0.3750\n",
      "Epoch 19/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.9677 - accuracy: 0.3750\n",
      "Epoch 20/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.9597 - accuracy: 0.3750\n",
      "Epoch 21/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.9519 - accuracy: 0.5000\n",
      "Epoch 22/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.9445 - accuracy: 0.3750\n",
      "Epoch 23/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.9374 - accuracy: 0.5000\n",
      "Epoch 24/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.9304 - accuracy: 0.3750\n",
      "Epoch 25/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.9238 - accuracy: 0.5000\n",
      "Epoch 26/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.9173 - accuracy: 0.5000\n",
      "Epoch 27/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.9111 - accuracy: 0.6250\n",
      "Epoch 28/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.9051 - accuracy: 0.5000\n",
      "Epoch 29/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.8993 - accuracy: 0.6250\n",
      "Epoch 30/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.8937 - accuracy: 0.5000\n",
      "Epoch 31/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.8882 - accuracy: 0.5000\n",
      "Epoch 32/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.8829 - accuracy: 0.5000\n",
      "Epoch 33/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.8778 - accuracy: 0.5000\n",
      "Epoch 34/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.8728 - accuracy: 0.5000\n",
      "Epoch 35/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.8680 - accuracy: 0.5000\n",
      "Epoch 36/200\n",
      "1/1 [==============================] - 0s 6ms/step - loss: 0.8633 - accuracy: 0.5000\n",
      "Epoch 37/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.8587 - accuracy: 0.5000\n",
      "Epoch 38/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.8543 - accuracy: 0.5000\n",
      "Epoch 39/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.8499 - accuracy: 0.5000\n",
      "Epoch 40/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.8457 - accuracy: 0.5000\n",
      "Epoch 41/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.8416 - accuracy: 0.5000\n",
      "Epoch 42/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.8377 - accuracy: 0.5000\n",
      "Epoch 43/200\n",
      "1/1 [==============================] - 0s 5ms/step - loss: 0.8338 - accuracy: 0.5000\n",
      "Epoch 44/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.8300 - accuracy: 0.5000\n",
      "Epoch 45/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.8263 - accuracy: 0.5000\n",
      "Epoch 46/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.8227 - accuracy: 0.5000\n",
      "Epoch 47/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.8191 - accuracy: 0.5000\n",
      "Epoch 48/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.8157 - accuracy: 0.5000\n",
      "Epoch 49/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.8123 - accuracy: 0.5000\n",
      "Epoch 50/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.8090 - accuracy: 0.5000\n",
      "Epoch 51/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.8058 - accuracy: 0.5000\n",
      "Epoch 52/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.8027 - accuracy: 0.5000\n",
      "Epoch 53/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.7996 - accuracy: 0.5000\n",
      "Epoch 54/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.7966 - accuracy: 0.5000\n",
      "Epoch 55/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.7936 - accuracy: 0.5000\n",
      "Epoch 56/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.7907 - accuracy: 0.6250\n",
      "Epoch 57/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.7878 - accuracy: 0.6250\n",
      "Epoch 58/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.7851 - accuracy: 0.6250\n",
      "Epoch 59/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.7823 - accuracy: 0.6250\n",
      "Epoch 60/200\n",
      "1/1 [==============================] - ETA: 0s - loss: 0.7796 - accuracy: 0.62 - 0s 4ms/step - loss: 0.7796 - accuracy: 0.6250\n",
      "Epoch 61/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.7770 - accuracy: 0.6250\n",
      "Epoch 62/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.7744 - accuracy: 0.6250\n",
      "Epoch 63/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.7719 - accuracy: 0.6250\n",
      "Epoch 64/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.7694 - accuracy: 0.6250\n",
      "Epoch 65/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.7669 - accuracy: 0.6250\n",
      "Epoch 66/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.7645 - accuracy: 0.6250\n",
      "Epoch 67/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.7621 - accuracy: 0.6250\n",
      "Epoch 68/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.7598 - accuracy: 0.6250\n",
      "Epoch 69/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.7575 - accuracy: 0.6250\n",
      "Epoch 70/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.7552 - accuracy: 0.6250\n",
      "Epoch 71/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.7530 - accuracy: 0.6250\n",
      "Epoch 72/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.7508 - accuracy: 0.6250\n",
      "Epoch 73/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.7486 - accuracy: 0.6250\n",
      "Epoch 74/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.7465 - accuracy: 0.6250\n",
      "Epoch 75/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.7444 - accuracy: 0.6250\n",
      "Epoch 76/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.7423 - accuracy: 0.6250\n",
      "Epoch 77/200\n",
      "1/1 [==============================] - 0s 1ms/step - loss: 0.7403 - accuracy: 0.6250\n",
      "Epoch 78/200\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1/1 [==============================] - 0s 2ms/step - loss: 0.7383 - accuracy: 0.6250\n",
      "Epoch 79/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.7363 - accuracy: 0.6250\n",
      "Epoch 80/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.7344 - accuracy: 0.6250\n",
      "Epoch 81/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.7324 - accuracy: 0.6250\n",
      "Epoch 82/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.7305 - accuracy: 0.6250\n",
      "Epoch 83/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.7287 - accuracy: 0.6250\n",
      "Epoch 84/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.7268 - accuracy: 0.6250\n",
      "Epoch 85/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.7250 - accuracy: 0.6250\n",
      "Epoch 86/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.7232 - accuracy: 0.6250\n",
      "Epoch 87/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.7214 - accuracy: 0.6250\n",
      "Epoch 88/200\n",
      "1/1 [==============================] - 0s 8ms/step - loss: 0.7197 - accuracy: 0.6250\n",
      "Epoch 89/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.7179 - accuracy: 0.6250\n",
      "Epoch 90/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.7162 - accuracy: 0.6250\n",
      "Epoch 91/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.7145 - accuracy: 0.6250\n",
      "Epoch 92/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.7128 - accuracy: 0.6250\n",
      "Epoch 93/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.7112 - accuracy: 0.6250\n",
      "Epoch 94/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.7096 - accuracy: 0.6250\n",
      "Epoch 95/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.7079 - accuracy: 0.6250\n",
      "Epoch 96/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.7063 - accuracy: 0.6250\n",
      "Epoch 97/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.7048 - accuracy: 0.6250\n",
      "Epoch 98/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.7032 - accuracy: 0.6250\n",
      "Epoch 99/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.7017 - accuracy: 0.6250\n",
      "Epoch 100/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.7001 - accuracy: 0.6250\n",
      "Epoch 101/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6986 - accuracy: 0.6250\n",
      "Epoch 102/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6971 - accuracy: 0.6250\n",
      "Epoch 103/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.6957 - accuracy: 0.6250\n",
      "Epoch 104/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6942 - accuracy: 0.6250\n",
      "Epoch 105/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6927 - accuracy: 0.6250\n",
      "Epoch 106/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6913 - accuracy: 0.6250\n",
      "Epoch 107/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6899 - accuracy: 0.6250\n",
      "Epoch 108/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6885 - accuracy: 0.6250\n",
      "Epoch 109/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6871 - accuracy: 0.6250\n",
      "Epoch 110/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6857 - accuracy: 0.6250\n",
      "Epoch 111/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6844 - accuracy: 0.6250\n",
      "Epoch 112/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.6830 - accuracy: 0.6250\n",
      "Epoch 113/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6817 - accuracy: 0.6250\n",
      "Epoch 114/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6804 - accuracy: 0.6250\n",
      "Epoch 115/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6790 - accuracy: 0.6250\n",
      "Epoch 116/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6777 - accuracy: 0.6250\n",
      "Epoch 117/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6765 - accuracy: 0.6250\n",
      "Epoch 118/200\n",
      "1/1 [==============================] - 0s 997us/step - loss: 0.6752 - accuracy: 0.6250\n",
      "Epoch 119/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6739 - accuracy: 0.6250\n",
      "Epoch 120/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6727 - accuracy: 0.6250\n",
      "Epoch 121/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6714 - accuracy: 0.6250\n",
      "Epoch 122/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6702 - accuracy: 0.6250\n",
      "Epoch 123/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.6690 - accuracy: 0.6250\n",
      "Epoch 124/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6678 - accuracy: 0.6250\n",
      "Epoch 125/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6666 - accuracy: 0.6250\n",
      "Epoch 126/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6654 - accuracy: 0.6250\n",
      "Epoch 127/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6642 - accuracy: 0.6250\n",
      "Epoch 128/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6631 - accuracy: 0.6250\n",
      "Epoch 129/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6619 - accuracy: 0.6250\n",
      "Epoch 130/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6608 - accuracy: 0.6250\n",
      "Epoch 131/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6596 - accuracy: 0.6250\n",
      "Epoch 132/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6585 - accuracy: 0.6250\n",
      "Epoch 133/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6574 - accuracy: 0.6250\n",
      "Epoch 134/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6563 - accuracy: 0.6250\n",
      "Epoch 135/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6552 - accuracy: 0.6250\n",
      "Epoch 136/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6541 - accuracy: 0.6250\n",
      "Epoch 137/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6530 - accuracy: 0.6250\n",
      "Epoch 138/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.6519 - accuracy: 0.6250\n",
      "Epoch 139/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6508 - accuracy: 0.6250\n",
      "Epoch 140/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.6498 - accuracy: 0.6250\n",
      "Epoch 141/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6487 - accuracy: 0.6250\n",
      "Epoch 142/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6477 - accuracy: 0.6250\n",
      "Epoch 143/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6467 - accuracy: 0.6250\n",
      "Epoch 144/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6456 - accuracy: 0.6250\n",
      "Epoch 145/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6446 - accuracy: 0.6250\n",
      "Epoch 146/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6436 - accuracy: 0.6250\n",
      "Epoch 147/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.6426 - accuracy: 0.6250\n",
      "Epoch 148/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6416 - accuracy: 0.6250\n",
      "Epoch 149/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6406 - accuracy: 0.6250\n",
      "Epoch 150/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6396 - accuracy: 0.6250\n",
      "Epoch 151/200\n",
      "1/1 [==============================] - 0s 1ms/step - loss: 0.6387 - accuracy: 0.6250\n",
      "Epoch 152/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6377 - accuracy: 0.6250\n",
      "Epoch 153/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6367 - accuracy: 0.6250\n",
      "Epoch 154/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6358 - accuracy: 0.6250\n",
      "Epoch 155/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6348 - accuracy: 0.6250\n",
      "Epoch 156/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6339 - accuracy: 0.6250\n",
      "Epoch 157/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6330 - accuracy: 0.7500\n",
      "Epoch 158/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6320 - accuracy: 0.7500\n",
      "Epoch 159/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6311 - accuracy: 0.7500\n",
      "Epoch 160/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6302 - accuracy: 0.7500\n",
      "Epoch 161/200\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6293 - accuracy: 0.7500\n",
      "Epoch 162/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.6284 - accuracy: 0.7500\n",
      "Epoch 163/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6275 - accuracy: 0.7500\n",
      "Epoch 164/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6266 - accuracy: 0.7500\n",
      "Epoch 165/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6257 - accuracy: 0.7500\n",
      "Epoch 166/200\n",
      "1/1 [==============================] - 0s 966us/step - loss: 0.6248 - accuracy: 0.7500\n",
      "Epoch 167/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.6240 - accuracy: 0.7500\n",
      "Epoch 168/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6231 - accuracy: 0.7500\n",
      "Epoch 169/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6222 - accuracy: 0.7500\n",
      "Epoch 170/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6214 - accuracy: 0.7500\n",
      "Epoch 171/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6205 - accuracy: 0.7500\n",
      "Epoch 172/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6197 - accuracy: 0.7500\n",
      "Epoch 173/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6188 - accuracy: 0.7500\n",
      "Epoch 174/200\n",
      "1/1 [==============================] - 0s 5ms/step - loss: 0.6180 - accuracy: 0.7500\n",
      "Epoch 175/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.6172 - accuracy: 0.7500\n",
      "Epoch 176/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6163 - accuracy: 0.7500\n",
      "Epoch 177/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6155 - accuracy: 0.7500\n",
      "Epoch 178/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.6147 - accuracy: 0.7500\n",
      "Epoch 179/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6139 - accuracy: 0.7500\n",
      "Epoch 180/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6131 - accuracy: 0.7500\n",
      "Epoch 181/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6123 - accuracy: 0.7500\n",
      "Epoch 182/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6115 - accuracy: 0.7500\n",
      "Epoch 183/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6107 - accuracy: 0.7500\n",
      "Epoch 184/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.6099 - accuracy: 0.7500\n",
      "Epoch 185/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.6091 - accuracy: 0.7500\n",
      "Epoch 186/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.6084 - accuracy: 0.7500\n",
      "Epoch 187/200\n",
      "1/1 [==============================] - 0s 5ms/step - loss: 0.6076 - accuracy: 0.7500\n",
      "Epoch 188/200\n",
      "1/1 [==============================] - 0s 7ms/step - loss: 0.6068 - accuracy: 0.7500\n",
      "Epoch 189/200\n",
      "1/1 [==============================] - 0s 6ms/step - loss: 0.6060 - accuracy: 0.7500\n",
      "Epoch 190/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.6053 - accuracy: 0.7500\n",
      "Epoch 191/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6045 - accuracy: 0.7500\n",
      "Epoch 192/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6038 - accuracy: 0.7500\n",
      "Epoch 193/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.6030 - accuracy: 0.7500\n",
      "Epoch 194/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6023 - accuracy: 0.7500\n",
      "Epoch 195/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.6015 - accuracy: 0.7500\n",
      "Epoch 196/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.6008 - accuracy: 0.7500\n",
      "Epoch 197/200\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.6001 - accuracy: 0.7500\n",
      "Epoch 198/200\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.5993 - accuracy: 0.7500\n",
      "Epoch 199/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.5986 - accuracy: 0.7500\n",
      "Epoch 200/200\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.5979 - accuracy: 0.7500\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.0181 - accuracy: 1.0000\n",
      "Predictions :  [2, 2, 2]\n",
      "Accuracy :  1.0\n"
     ]
    }
   ],
   "source": [
    "from keras.models import Sequential\n",
    "from keras.layers import Dense, Activation\n",
    "from keras.optimizers import SGD\n",
    "import numpy as np\n",
    "np.random.seed(777)\n",
    "\n",
    "x_data = np.array([[1, 2, 1], [1, 3, 2], [1, 3, 4], [1, 5, 5], [1, 7, 5], [1, 2, 5], [1, 6, 6], [1, 7, 7]])\n",
    "y_data = np.array([[0, 0, 1], [0, 0, 1], [0, 0, 1], [0, 1, 0], [0, 1, 0], [0, 1, 0], [1, 0, 0], [1, 0, 0]])\n",
    "\n",
    "# Evaluation our model using this test dataset\n",
    "x_test = np.array([[2, 1, 1], [3, 1, 2], [3, 3, 4]])\n",
    "y_test = np.array([[0, 0, 1], [0, 0, 1], [0, 0, 1]])\n",
    "\n",
    "model = Sequential()\n",
    "model.add(Dense(3, input_dim=3))\n",
    "model.add(Activation('softmax'))\n",
    "\n",
    "model.summary()\n",
    "\n",
    "model.compile(loss='categorical_crossentropy',\n",
    "             optimizer=SGD(lr=0.1),\n",
    "             metrics=['accuracy'])\n",
    "\n",
    "history = model.fit(x_data, y_data, epochs = 200)\n",
    "\n",
    "predictions = model.predict(x_test)\n",
    "score = model.evaluate(x_test, y_test)\n",
    "\n",
    "print('Predictions : ', [np.argmax(prediction) for prediction in predictions])\n",
    "print('Accuracy : ', score[1])\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1.         1.         0.         1.         1.        ]\n",
      " [0.70548491 0.70439552 1.         0.71881783 0.83755792]\n",
      " [0.54412549 0.50274824 0.57608696 0.60646801 0.6606331 ]\n",
      " [0.33890353 0.31368023 0.10869565 0.45989134 0.43800918]\n",
      " [0.51436    0.4258239  0.30434783 0.58504805 0.42624401]\n",
      " [0.49556179 0.4258239  0.31521739 0.48131134 0.49276137]\n",
      " [0.11436064 0.         0.20652174 0.22007776 0.18597238]\n",
      " [0.         0.07747099 0.5326087  0.         0.        ]]\n",
      "Model: \"sequential_15\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "dense_15 (Dense)             (None, 1)                 5         \n",
      "_________________________________________________________________\n",
      "activation_15 (Activation)   (None, 1)                 0         \n",
      "=================================================================\n",
      "Total params: 5\n",
      "Trainable params: 5\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n",
      "Epoch 1/100\n",
      "1/1 [==============================] - 0s 5ms/step - loss: 0.4432 - accuracy: 0.2500\n",
      "Epoch 2/100\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.4200 - accuracy: 0.2500\n",
      "Epoch 3/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.3985 - accuracy: 0.2500\n",
      "Epoch 4/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.3786 - accuracy: 0.2500\n",
      "Epoch 5/100\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.3601 - accuracy: 0.2500\n",
      "Epoch 6/100\n",
      "1/1 [==============================] - 0s 5ms/step - loss: 0.3429 - accuracy: 0.2500\n",
      "Epoch 7/100\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.3269 - accuracy: 0.2500\n",
      "Epoch 8/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.3121 - accuracy: 0.2500\n",
      "Epoch 9/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.2983 - accuracy: 0.2500\n",
      "Epoch 10/100\n",
      "1/1 [==============================] - 0s 5ms/step - loss: 0.2855 - accuracy: 0.2500\n",
      "Epoch 11/100\n",
      "1/1 [==============================] - 0s 5ms/step - loss: 0.2736 - accuracy: 0.2500\n",
      "Epoch 12/100\n",
      "1/1 [==============================] - 0s 5ms/step - loss: 0.2626 - accuracy: 0.2500\n",
      "Epoch 13/100\n",
      "1/1 [==============================] - 0s 5ms/step - loss: 0.2523 - accuracy: 0.2500\n",
      "Epoch 14/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.2427 - accuracy: 0.2500\n",
      "Epoch 15/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.2338 - accuracy: 0.2500\n",
      "Epoch 16/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.2255 - accuracy: 0.2500\n",
      "Epoch 17/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.2178 - accuracy: 0.2500\n",
      "Epoch 18/100\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.2106 - accuracy: 0.2500\n",
      "Epoch 19/100\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.2038 - accuracy: 0.2500\n",
      "Epoch 20/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.1975 - accuracy: 0.2500\n",
      "Epoch 21/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.1917 - accuracy: 0.2500\n",
      "Epoch 22/100\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.1862 - accuracy: 0.2500\n",
      "Epoch 23/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.1811 - accuracy: 0.2500\n",
      "Epoch 24/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.1763 - accuracy: 0.2500\n",
      "Epoch 25/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.1718 - accuracy: 0.2500\n",
      "Epoch 26/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.1676 - accuracy: 0.2500\n",
      "Epoch 27/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.1637 - accuracy: 0.2500\n",
      "Epoch 28/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.1600 - accuracy: 0.2500\n",
      "Epoch 29/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.1565 - accuracy: 0.2500\n",
      "Epoch 30/100\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.1532 - accuracy: 0.2500\n",
      "Epoch 31/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.1502 - accuracy: 0.2500\n",
      "Epoch 32/100\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.1473 - accuracy: 0.2500\n",
      "Epoch 33/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.1445 - accuracy: 0.2500\n",
      "Epoch 34/100\n",
      "1/1 [==============================] - 0s 5ms/step - loss: 0.1420 - accuracy: 0.2500\n",
      "Epoch 35/100\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.1395 - accuracy: 0.2500\n",
      "Epoch 36/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.1372 - accuracy: 0.2500\n",
      "Epoch 37/100\n",
      "1/1 [==============================] - 0s 5ms/step - loss: 0.1351 - accuracy: 0.2500\n",
      "Epoch 38/100\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.1330 - accuracy: 0.2500\n",
      "Epoch 39/100\n",
      "1/1 [==============================] - 0s 1ms/step - loss: 0.1311 - accuracy: 0.2500\n",
      "Epoch 40/100\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.1292 - accuracy: 0.2500\n",
      "Epoch 41/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.1274 - accuracy: 0.2500\n",
      "Epoch 42/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.1257 - accuracy: 0.2500\n",
      "Epoch 43/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.1241 - accuracy: 0.2500\n",
      "Epoch 44/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.1226 - accuracy: 0.2500\n",
      "Epoch 45/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.1211 - accuracy: 0.2500\n",
      "Epoch 46/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.1197 - accuracy: 0.2500\n",
      "Epoch 47/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.1184 - accuracy: 0.2500\n",
      "Epoch 48/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.1171 - accuracy: 0.2500\n",
      "Epoch 49/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.1159 - accuracy: 0.2500\n",
      "Epoch 50/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.1147 - accuracy: 0.2500\n",
      "Epoch 51/100\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.1135 - accuracy: 0.2500\n",
      "Epoch 52/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.1124 - accuracy: 0.2500\n",
      "Epoch 53/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.1114 - accuracy: 0.2500\n",
      "Epoch 54/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.1103 - accuracy: 0.2500\n",
      "Epoch 55/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.1093 - accuracy: 0.2500\n",
      "Epoch 56/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.1084 - accuracy: 0.2500\n",
      "Epoch 57/100\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.1074 - accuracy: 0.2500\n",
      "Epoch 58/100\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.1065 - accuracy: 0.2500\n",
      "Epoch 59/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.1056 - accuracy: 0.2500\n",
      "Epoch 60/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.1048 - accuracy: 0.2500\n",
      "Epoch 61/100\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.1039 - accuracy: 0.2500\n",
      "Epoch 62/100\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.1031 - accuracy: 0.2500\n",
      "Epoch 63/100\n",
      "1/1 [==============================] - 0s 997us/step - loss: 0.1023 - accuracy: 0.2500\n",
      "Epoch 64/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.1015 - accuracy: 0.2500\n",
      "Epoch 65/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.1008 - accuracy: 0.2500\n",
      "Epoch 66/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.1000 - accuracy: 0.2500\n",
      "Epoch 67/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.0993 - accuracy: 0.2500\n",
      "Epoch 68/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.0986 - accuracy: 0.2500\n",
      "Epoch 69/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.0979 - accuracy: 0.2500\n",
      "Epoch 70/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.0972 - accuracy: 0.2500\n",
      "Epoch 71/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.0965 - accuracy: 0.2500\n",
      "Epoch 72/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.0958 - accuracy: 0.2500\n",
      "Epoch 73/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1/1 [==============================] - 0s 2ms/step - loss: 0.0952 - accuracy: 0.2500\n",
      "Epoch 74/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.0945 - accuracy: 0.2500\n",
      "Epoch 75/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.0939 - accuracy: 0.2500\n",
      "Epoch 76/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.0932 - accuracy: 0.2500\n",
      "Epoch 77/100\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.0926 - accuracy: 0.2500\n",
      "Epoch 78/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.0920 - accuracy: 0.2500\n",
      "Epoch 79/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.0914 - accuracy: 0.2500\n",
      "Epoch 80/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.0908 - accuracy: 0.2500\n",
      "Epoch 81/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.0902 - accuracy: 0.2500\n",
      "Epoch 82/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.0896 - accuracy: 0.2500\n",
      "Epoch 83/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.0891 - accuracy: 0.2500\n",
      "Epoch 84/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.0885 - accuracy: 0.2500\n",
      "Epoch 85/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.0879 - accuracy: 0.2500\n",
      "Epoch 86/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.0874 - accuracy: 0.2500\n",
      "Epoch 87/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.0868 - accuracy: 0.2500\n",
      "Epoch 88/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.0863 - accuracy: 0.2500\n",
      "Epoch 89/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.0857 - accuracy: 0.2500\n",
      "Epoch 90/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.0852 - accuracy: 0.2500\n",
      "Epoch 91/100\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.0847 - accuracy: 0.2500\n",
      "Epoch 92/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.0842 - accuracy: 0.2500\n",
      "Epoch 93/100\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.0836 - accuracy: 0.2500\n",
      "Epoch 94/100\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.0831 - accuracy: 0.2500\n",
      "Epoch 95/100\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.0826 - accuracy: 0.2500\n",
      "Epoch 96/100\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.0821 - accuracy: 0.2500\n",
      "Epoch 97/100\n",
      "1/1 [==============================] - 0s 4ms/step - loss: 0.0816 - accuracy: 0.2500\n",
      "Epoch 98/100\n",
      "1/1 [==============================] - ETA: 0s - loss: 0.0811 - accuracy: 0.25 - 0s 4ms/step - loss: 0.0811 - accuracy: 0.2500\n",
      "Epoch 99/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.0806 - accuracy: 0.2500\n",
      "Epoch 100/100\n",
      "1/1 [==============================] - 0s 2ms/step - loss: 0.0801 - accuracy: 0.2500\n",
      "WARNING:tensorflow:11 out of the last 11 calls to <function Model.make_predict_function.<locals>.predict_function at 0x000001D903412670> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
      "WARNING:tensorflow:11 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x000001D9034128B0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
      "1/1 [==============================] - 0s 3ms/step - loss: 0.0796 - accuracy: 0.2500\n",
      "Predictions :  [[ 1.5853381 ]\n",
      " [ 0.6067097 ]\n",
      " [ 0.5278755 ]\n",
      " [ 0.43760163]\n",
      " [ 0.57666945]\n",
      " [ 0.4953552 ]\n",
      " [-0.07330345]\n",
      " [-0.36561218]]\n",
      "Cost :  0.07963338494300842\n"
     ]
    }
   ],
   "source": [
    "from keras.models import Sequential\n",
    "from keras.layers import Dense, Activation\n",
    "from keras.optimizers import SGD\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "import numpy as np\n",
    "np.random.seed(777)\n",
    "\n",
    "xy = np.array([[828.659973, 833.450012, 908100, 828.349976, 831.659973],\n",
    "               [823.02002, 828.070007, 1828100, 821.655029, 828.070007],\n",
    "               [819.929993, 824.400024, 1438100, 818.97998, 824.159973],\n",
    "               [816, 820.958984, 1008100, 815.48999, 819.23999],\n",
    "               [819.359985, 823, 1188100, 818.469971, 818.97998],\n",
    "               [819, 823, 1198100, 816, 820.450012],\n",
    "               [811.700012, 815.25, 1098100, 809.780029, 813.669983],\n",
    "               [809.51001, 816.659973, 1398100, 804.539978, 809.559998]])\n",
    "\n",
    "#정규화\n",
    "scaler = MinMaxScaler(feature_range = (0, 1))\n",
    "xy = scaler.fit_transform(xy)\n",
    "print(xy)\n",
    "\n",
    "x_data = xy[:, 0:-1]\n",
    "y_data = xy[:, [-1]]\n",
    "\n",
    "model = Sequential()\n",
    "model.add(Dense(1, input_dim = 4))\n",
    "model.add(Activation('linear'))\n",
    "\n",
    "model.summary()\n",
    "\n",
    "model.compile(loss = 'mse',\n",
    "             optimizer = 'sgd',\n",
    "             metrics = ['accuracy'])\n",
    "\n",
    "history = model.fit(x_data, y_data, epochs = 100)\n",
    "\n",
    "predictions = model.predict(x_data)\n",
    "score = model.evaluate(x_data, y_data)\n",
    "\n",
    "print('Predictions : ', predictions)\n",
    "print('Cost : ', score[0])\n"
   ]
  }
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