TF 8 Titanic using Tensorflow tflearn.ipynb

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  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "curses is not supported on this machine (please install/reinstall curses for an optimal experience)\n"
     ]
    }
   ],
   "source": [
    "import tflearn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from tflearn.datasets import titanic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'./titanic_dataset.csv'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.download_dataset('titanic_dataset.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from tflearn.data_utils import load_csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data, labels = load_csv('titanic_dataset.csv',target_column=0, categorical_labels=True, n_classes=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.,  1.],\n",
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       "       [ 1.,  0.],\n",
       "       ..., \n",
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       "       [ 1.,  0.],\n",
       "       [ 1.,  0.]])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
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       "  '14.4542'],\n",
       " ['3', 'Kiernan, Mr. John', 'male', '0', '1', '0', '367227', '7.7500'],\n",
       " ['3', 'Kiernan, Mr. Philip', 'male', '0', '1', '0', '367229', '7.7500'],\n",
       " ['3', 'Kilgannon, Mr. Thomas J', 'male', '0', '0', '0', '36865', '7.7375'],\n",
       " ['3', 'Kink, Miss. Maria', 'female', '22', '2', '0', '315152', '8.6625'],\n",
       " ['3', 'Kink, Mr. Vincenz', 'male', '26', '2', '0', '315151', '8.6625'],\n",
       " ['3',\n",
       "  'Kink-Heilmann, Miss. Luise Gretchen',\n",
       "  'female',\n",
       "  '4',\n",
       "  '0',\n",
       "  '2',\n",
       "  '315153',\n",
       "  '22.0250'],\n",
       " ['3',\n",
       "  'Kink-Heilmann, Mr. Anton',\n",
       "  'male',\n",
       "  '29',\n",
       "  '3',\n",
       "  '1',\n",
       "  '315153',\n",
       "  '22.0250'],\n",
       " ['3',\n",
       "  'Kink-Heilmann, Mrs. Anton (Luise Heilmann)',\n",
       "  'female',\n",
       "  '26',\n",
       "  '1',\n",
       "  '1',\n",
       "  '315153',\n",
       "  '22.0250'],\n",
       " ['3',\n",
       "  'Klasen, Miss. Gertrud Emilia',\n",
       "  'female',\n",
       "  '1',\n",
       "  '1',\n",
       "  '1',\n",
       "  '350405',\n",
       "  '12.1833'],\n",
       " ['3', 'Klasen, Mr. Klas Albin', 'male', '18', '1', '1', '350404', '7.8542'],\n",
       " ['3',\n",
       "  'Klasen, Mrs. (Hulda Kristina Eugenia Lofqvist)',\n",
       "  'female',\n",
       "  '36',\n",
       "  '0',\n",
       "  '2',\n",
       "  '350405',\n",
       "  '12.1833'],\n",
       " ['3', 'Kraeff, Mr. Theodor', 'male', '0', '0', '0', '349253', '7.8958'],\n",
       " ['3', 'Krekorian, Mr. Neshan', 'male', '25', '0', '0', '2654', '7.2292'],\n",
       " ['3', 'Lahoud, Mr. Sarkis', 'male', '0', '0', '0', '2624', '7.2250'],\n",
       " ['3',\n",
       "  'Laitinen, Miss. Kristina Sofia',\n",
       "  'female',\n",
       "  '37',\n",
       "  '0',\n",
       "  '0',\n",
       "  '4135',\n",
       "  '9.5875'],\n",
       " ['3', 'Laleff, Mr. Kristo', 'male', '0', '0', '0', '349217', '7.8958'],\n",
       " ['3', 'Lam, Mr. Ali', 'male', '0', '0', '0', '1601', '56.4958'],\n",
       " ['3', 'Lam, Mr. Len', 'male', '0', '0', '0', '1601', '56.4958'],\n",
       " ['3',\n",
       "  'Landergren, Miss. Aurora Adelia',\n",
       "  'female',\n",
       "  '22',\n",
       "  '0',\n",
       "  '0',\n",
       "  'C 7077',\n",
       "  '7.2500'],\n",
       " ['3', 'Lane, Mr. Patrick', 'male', '0', '0', '0', '7935', '7.7500'],\n",
       " ['3', 'Lang, Mr. Fang', 'male', '26', '0', '0', '1601', '56.4958'],\n",
       " ['3', 'Larsson, Mr. August Viktor', 'male', '29', '0', '0', '7545', '9.4833'],\n",
       " ['3', 'Larsson, Mr. Bengt Edvin', 'male', '29', '0', '0', '347067', '7.7750'],\n",
       " ['3',\n",
       "  'Larsson-Rondberg, Mr. Edvard A',\n",
       "  'male',\n",
       "  '22',\n",
       "  '0',\n",
       "  '0',\n",
       "  '347065',\n",
       "  '7.7750'],\n",
       " ['3',\n",
       "  'Leeni, Mr. Fahim (\"Philip Zenni\")',\n",
       "  'male',\n",
       "  '22',\n",
       "  '0',\n",
       "  '0',\n",
       "  '2620',\n",
       "  '7.2250'],\n",
       " ['3',\n",
       "  'Lefebre, Master. Henry Forbes',\n",
       "  'male',\n",
       "  '0',\n",
       "  '3',\n",
       "  '1',\n",
       "  '4133',\n",
       "  '25.4667'],\n",
       " ['3', 'Lefebre, Miss. Ida', 'female', '0', '3', '1', '4133', '25.4667'],\n",
       " ['3', 'Lefebre, Miss. Jeannie', 'female', '0', '3', '1', '4133', '25.4667'],\n",
       " ['3', 'Lefebre, Miss. Mathilde', 'female', '0', '3', '1', '4133', '25.4667'],\n",
       " ['3',\n",
       "  'Lefebre, Mrs. Frank (Frances)',\n",
       "  'female',\n",
       "  '0',\n",
       "  '0',\n",
       "  '4',\n",
       "  '4133',\n",
       "  '25.4667'],\n",
       " ['3',\n",
       "  'Leinonen, Mr. Antti Gustaf',\n",
       "  'male',\n",
       "  '32',\n",
       "  '0',\n",
       "  '0',\n",
       "  'STON/O 2. 3101292',\n",
       "  '7.9250'],\n",
       " ['3',\n",
       "  'Lemberopolous, Mr. Peter L',\n",
       "  'male',\n",
       "  '34.5',\n",
       "  '0',\n",
       "  '0',\n",
       "  '2683',\n",
       "  '6.4375'],\n",
       " ['3', 'Lennon, Miss. Mary', 'female', '0', '1', '0', '370371', '15.5000'],\n",
       " ['3', 'Lennon, Mr. Denis', 'male', '0', '1', '0', '370371', '15.5000'],\n",
       " ['3', 'Leonard, Mr. Lionel', 'male', '36', '0', '0', 'LINE', '0.0000'],\n",
       " ['3', 'Lester, Mr. James', 'male', '39', '0', '0', 'A/4 48871', '24.1500'],\n",
       " ['3', 'Lievens, Mr. Rene Aime', 'male', '24', '0', '0', '345781', '9.5000'],\n",
       " ['3',\n",
       "  'Lindahl, Miss. Agda Thorilda Viktoria',\n",
       "  'female',\n",
       "  '25',\n",
       "  '0',\n",
       "  '0',\n",
       "  '347071',\n",
       "  '7.7750'],\n",
       " ['3',\n",
       "  'Lindblom, Miss. Augusta Charlotta',\n",
       "  'female',\n",
       "  '45',\n",
       "  '0',\n",
       "  '0',\n",
       "  '347073',\n",
       "  '7.7500'],\n",
       " ['3',\n",
       "  'Lindell, Mr. Edvard Bengtsson',\n",
       "  'male',\n",
       "  '36',\n",
       "  '1',\n",
       "  '0',\n",
       "  '349910',\n",
       "  '15.5500'],\n",
       " ['3',\n",
       "  'Lindell, Mrs. Edvard Bengtsson (Elin Gerda Persson)',\n",
       "  'female',\n",
       "  '30',\n",
       "  '1',\n",
       "  '0',\n",
       "  '349910',\n",
       "  '15.5500'],\n",
       " ['3',\n",
       "  'Lindqvist, Mr. Eino William',\n",
       "  'male',\n",
       "  '20',\n",
       "  '1',\n",
       "  '0',\n",
       "  'STON/O 2. 3101285',\n",
       "  '7.9250'],\n",
       " ['3', 'Linehan, Mr. Michael', 'male', '0', '0', '0', '330971', '7.8792'],\n",
       " ['3', 'Ling, Mr. Lee', 'male', '28', '0', '0', '1601', '56.4958'],\n",
       " ['3', 'Lithman, Mr. Simon', 'male', '0', '0', '0', 'S.O./P.P. 251', '7.5500'],\n",
       " ['3',\n",
       "  'Lobb, Mr. William Arthur',\n",
       "  'male',\n",
       "  '30',\n",
       "  '1',\n",
       "  '0',\n",
       "  'A/5. 3336',\n",
       "  '16.1000'],\n",
       " ['3',\n",
       "  'Lobb, Mrs. William Arthur (Cordelia K Stanlick)',\n",
       "  'female',\n",
       "  '26',\n",
       "  '1',\n",
       "  '0',\n",
       "  'A/5. 3336',\n",
       "  '16.1000'],\n",
       " ['3', 'Lockyer, Mr. Edward', 'male', '0', '0', '0', '1222', '7.8792'],\n",
       " ['3',\n",
       "  'Lovell, Mr. John Hall (\"Henry\")',\n",
       "  'male',\n",
       "  '20.5',\n",
       "  '0',\n",
       "  '0',\n",
       "  'A/5 21173',\n",
       "  '7.2500'],\n",
       " ['3', 'Lulic, Mr. Nikola', 'male', '27', '0', '0', '315098', '8.6625'],\n",
       " ['3',\n",
       "  'Lundahl, Mr. Johan Svensson',\n",
       "  'male',\n",
       "  '51',\n",
       "  '0',\n",
       "  '0',\n",
       "  '347743',\n",
       "  '7.0542'],\n",
       " ['3',\n",
       "  'Lundin, Miss. Olga Elida',\n",
       "  'female',\n",
       "  '23',\n",
       "  '0',\n",
       "  '0',\n",
       "  '347469',\n",
       "  '7.8542'],\n",
       " ['3',\n",
       "  'Lundstrom, Mr. Thure Edvin',\n",
       "  'male',\n",
       "  '32',\n",
       "  '0',\n",
       "  '0',\n",
       "  '350403',\n",
       "  '7.5792'],\n",
       " ['3', 'Lyntakoff, Mr. Stanko', 'male', '0', '0', '0', '349235', '7.8958'],\n",
       " ['3',\n",
       "  'MacKay, Mr. George William',\n",
       "  'male',\n",
       "  '0',\n",
       "  '0',\n",
       "  '0',\n",
       "  'C.A. 42795',\n",
       "  '7.5500'],\n",
       " ['3',\n",
       "  'Madigan, Miss. Margaret \"Maggie\"',\n",
       "  'female',\n",
       "  '0',\n",
       "  '0',\n",
       "  '0',\n",
       "  '370370',\n",
       "  '7.7500'],\n",
       " ['3',\n",
       "  'Madsen, Mr. Fridtjof Arne',\n",
       "  'male',\n",
       "  '24',\n",
       "  '0',\n",
       "  '0',\n",
       "  'C 17369',\n",
       "  '7.1417'],\n",
       " ['3',\n",
       "  'Maenpaa, Mr. Matti Alexanteri',\n",
       "  'male',\n",
       "  '22',\n",
       "  '0',\n",
       "  '0',\n",
       "  'STON/O 2. 3101275',\n",
       "  '7.1250'],\n",
       " ['3',\n",
       "  'Mahon, Miss. Bridget Delia',\n",
       "  'female',\n",
       "  '0',\n",
       "  '0',\n",
       "  '0',\n",
       "  '330924',\n",
       "  '7.8792'],\n",
       " ['3', 'Mahon, Mr. John', 'male', '0', '0', '0', 'AQ/4 3130', '7.7500'],\n",
       " ['3', 'Maisner, Mr. Simon', 'male', '0', '0', '0', 'A/S 2816', '8.0500'],\n",
       " ['3',\n",
       "  'Makinen, Mr. Kalle Edvard',\n",
       "  'male',\n",
       "  '29',\n",
       "  '0',\n",
       "  '0',\n",
       "  'STON/O 2. 3101268',\n",
       "  '7.9250'],\n",
       " ['3', 'Mamee, Mr. Hanna', 'male', '0', '0', '0', '2677', '7.2292'],\n",
       " ['3', 'Mangan, Miss. Mary', 'female', '30.5', '0', '0', '364850', '7.7500'],\n",
       " ['3', 'Mannion, Miss. Margareth', 'female', '0', '0', '0', '36866', '7.7375'],\n",
       " ['3', 'Mardirosian, Mr. Sarkis', 'male', '0', '0', '0', '2655', '7.2292'],\n",
       " ['3', 'Markoff, Mr. Marin', 'male', '35', '0', '0', '349213', '7.8958'],\n",
       " ['3', 'Markun, Mr. Johann', 'male', '33', '0', '0', '349257', '7.8958'],\n",
       " ['3', 'Masselmani, Mrs. Fatima', 'female', '0', '0', '0', '2649', '7.2250'],\n",
       " ['3', 'Matinoff, Mr. Nicola', 'male', '0', '0', '0', '349255', '7.8958'],\n",
       " ['3',\n",
       "  'McCarthy, Miss. Catherine \"Katie\"',\n",
       "  'female',\n",
       "  '0',\n",
       "  '0',\n",
       "  '0',\n",
       "  '383123',\n",
       "  '7.7500'],\n",
       " ...]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Preprocess the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def preprocess(data,columns_to_ignore):\n",
    "    #delete col 1 & 6\n",
    "    for id in sorted(columns_to_ignore,reverse=True):\n",
    "        [r.pop(id) for r in data]\n",
    "    \n",
    "    for i in range(len(data)):\n",
    "        if data[i][1] == 'female':\n",
    "            data[i][1] = 1\n",
    "        else:\n",
    "            data[i][1] = 0\n",
    "    return np.array(data, dtype=np.float32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data = preprocess(data,[1,6])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1309, 6)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Build the deep neural network"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "net = tflearn.input_data(shape=[None,6])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "net = tflearn.fully_connected(net,32)\n",
    "net = tflearn.fully_connected(net,32)\n",
    "net = tflearn.fully_connected(net,32)\n",
    "net = tflearn.fully_connected(net,2,activation='softmax')\n",
    "net = tflearn.regression(net)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "model = tflearn.DNN(net)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Step: 819  | total loss: \u001b[1m\u001b[32m0.54876\u001b[0m\u001b[0m | time: 1.387s\n",
      "| Adam | epoch: 010 | loss: 0.54876 - acc: 0.7249 -- iter: 1296/1309\n",
      "Training Step: 820  | total loss: \u001b[1m\u001b[32m0.53130\u001b[0m\u001b[0m | time: 1.400s\n",
      "| Adam | epoch: 010 | loss: 0.53130 - acc: 0.7337 -- iter: 1309/1309\n",
      "--\n"
     ]
    }
   ],
   "source": [
    "model.fit(data,labels,n_epoch=10, batch_size=16, show_metric=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dicaprio = [3, 'Jack Dawson', 'male', 19, 0, 0, 'N/A', 5.0000]\n",
    "winslet = [1, 'Rose DeWitt Bukater', 'female', 17, 1, 2, 'N/A', 100.0000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dicaprio, winslet = preprocess([dicaprio,winslet],[1,6])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.84191197,  0.15808806],\n",
       "       [ 0.08510479,  0.91489518]], dtype=float32)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.predict([dicaprio,winslet])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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