penguine.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   Region  Island  cc    cl    cd     fl      bm  Sex\n",
      "0       0       0   1  39.3  20.6  190.0  3650.0  0.0\n",
      "1       0       0   0  38.9  17.8  181.0  3625.0  1.0\n",
      "2       0       0   0  39.2  19.6  195.0  4675.0  0.0\n",
      "3       0       0   1  34.1  18.1  193.0  3475.0  0.0\n",
      "4       0       0   1  42.0  20.2  190.0  4250.0  0.0\n",
      "0     0\n",
      "1     0\n",
      "2     0\n",
      "3     0\n",
      "4     0\n",
      "5     0\n",
      "6     0\n",
      "7     0\n",
      "8     0\n",
      "9     0\n",
      "10    0\n",
      "11    0\n",
      "12    0\n",
      "13    0\n",
      "14    0\n",
      "15    0\n",
      "16    0\n",
      "17    0\n",
      "18    0\n",
      "19    0\n",
      "20    0\n",
      "21    0\n",
      "22    0\n",
      "23    0\n",
      "24    0\n",
      "25    0\n",
      "26    0\n",
      "27    0\n",
      "28    0\n",
      "29    0\n",
      "30    0\n",
      "31    0\n",
      "32    0\n",
      "33    0\n",
      "34    0\n",
      "35    0\n",
      "36    0\n",
      "37    0\n",
      "38    0\n",
      "39    0\n",
      "40    0\n",
      "41    0\n",
      "42    0\n",
      "43    0\n",
      "44    0\n",
      "45    0\n",
      "46    0\n",
      "47    0\n",
      "48    1\n",
      "49    1\n",
      "50    1\n",
      "51    1\n",
      "52    1\n",
      "53    1\n",
      "54    1\n",
      "55    1\n",
      "56    1\n",
      "57    1\n",
      "58    1\n",
      "59    1\n",
      "60    1\n",
      "61    1\n",
      "62    1\n",
      "63    1\n",
      "64    1\n",
      "65    1\n",
      "66    1\n",
      "67    2\n",
      "68    2\n",
      "69    2\n",
      "70    2\n",
      "71    2\n",
      "72    2\n",
      "73    2\n",
      "74    2\n",
      "Name: Species, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "#changes22\n",
    "import pandas as pd\n",
    "from IPython.display import clear_output\n",
    "import tensorflow as tf\n",
    "from sklearn.impute import SimpleImputer\n",
    "pd.set_option('display.max_rows', None)\n",
    "pd.set_option('display.max_columns', None)\n",
    "pd.set_option('display.width', None)\n",
    "dftrain = pd.read_csv('data/penguins_train.csv') # training data\n",
    "dfeval = pd.read_csv('data/penguins_eval.csv') # testing data\n",
    "\n",
    "#setting strategy to 'most frequent' to impute by the mean\n",
    "imputer = SimpleImputer(strategy='most_frequent')# strategy can also be mean or median \n",
    "dftrain.iloc[:,:] = imputer.fit_transform(dftrain)\n",
    "dftrain.isnull().sum()\n",
    "\n",
    "y_train = dftrain.pop('Species')\n",
    "y_eval = dfeval.pop('Species')\n",
    "print(dftrain.head())\n",
    "y_train = y_train.replace(\"Adelie Penguin (Pygoscelis adeliae)\",0)\n",
    "y_train = y_train.replace(\"Chinstrap penguin (Pygoscelis antarctica)\",1)\n",
    "y_train = y_train.replace(\"Gentoo penguin (Pygoscelis papua)\",2)\n",
    "y_eval = y_eval.replace(\"Adelie Penguin (Pygoscelis adeliae)\",0)\n",
    "y_eval = y_eval.replace(\"Chinstrap penguin (Pygoscelis antarctica)\",1)\n",
    "y_eval = y_eval.replace(\"Gentoo penguin (Pygoscelis papua)\",2)\n",
    "print(y_eval)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[NumericColumn(key='Region', shape=(1,), default_value=None, dtype=tf.float32, normalizer_fn=None), NumericColumn(key='Island', shape=(1,), default_value=None, dtype=tf.float32, normalizer_fn=None), NumericColumn(key='cc', shape=(1,), default_value=None, dtype=tf.float32, normalizer_fn=None), NumericColumn(key='cl', shape=(1,), default_value=None, dtype=tf.float32, normalizer_fn=None), NumericColumn(key='cd', shape=(1,), default_value=None, dtype=tf.float32, normalizer_fn=None), NumericColumn(key='fl', shape=(1,), default_value=None, dtype=tf.float32, normalizer_fn=None), NumericColumn(key='bm', shape=(1,), default_value=None, dtype=tf.float32, normalizer_fn=None), NumericColumn(key='Sex', shape=(1,), default_value=None, dtype=tf.float32, normalizer_fn=None)]\n",
      "INFO:tensorflow:Using default config.\n",
      "WARNING:tensorflow:Using temporary folder as model directory: C:\\Users\\priya\\AppData\\Local\\Temp\\tmp1u_1hrec\n",
      "INFO:tensorflow:Using config: {'_model_dir': 'C:\\\\Users\\\\priya\\\\AppData\\\\Local\\\\Temp\\\\tmp1u_1hrec', '_tf_random_seed': None, '_save_summary_steps': 100, '_save_checkpoints_steps': None, '_save_checkpoints_secs': 600, '_session_config': allow_soft_placement: true\n",
      "graph_options {\n",
      "  rewrite_options {\n",
      "    meta_optimizer_iterations: ONE\n",
      "  }\n",
      "}\n",
      ", '_keep_checkpoint_max': 5, '_keep_checkpoint_every_n_hours': 10000, '_log_step_count_steps': 100, '_train_distribute': None, '_device_fn': None, '_protocol': None, '_eval_distribute': None, '_experimental_distribute': None, '_experimental_max_worker_delay_secs': None, '_session_creation_timeout_secs': 7200, '_checkpoint_save_graph_def': True, '_service': None, '_cluster_spec': ClusterSpec({}), '_task_type': 'worker', '_task_id': 0, '_global_id_in_cluster': 0, '_master': '', '_evaluation_master': '', '_is_chief': True, '_num_ps_replicas': 0, '_num_worker_replicas': 1}\n"
     ]
    }
   ],
   "source": [
    "def input_fn(features, labels, training=True, batch_size=256):\n",
    "    # Convert the inputs to a Dataset.\n",
    "    dataset = tf.data.Dataset.from_tensor_slices((dict(features), labels))\n",
    "\n",
    "    # Shuffle and repeat if you are in training mode.\n",
    "    if training:\n",
    "        dataset = dataset.shuffle(1000).repeat()\n",
    "\n",
    "    return dataset.batch(batch_size)\n",
    "\n",
    "# Feature columns describe how to use the input.\n",
    "my_feature_columns = []\n",
    "for key in dftrain.keys():\n",
    "    my_feature_columns.append(tf.feature_column.numeric_column(key=key))\n",
    "print(my_feature_columns)\n",
    "\n",
    "# Build a DNN with 2 hidden layers with 30 and 10 hidden nodes each.\n",
    "classifier = tf.estimator.DNNClassifier(\n",
    "    feature_columns=my_feature_columns,\n",
    "    # Two hidden layers of 30 and 10 nodes respectively.\n",
    "    hidden_units=[60, 20],\n",
    "    # The model must choose between 3 classes.\n",
    "    n_classes=3)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Calling model_fn.\n",
      "INFO:tensorflow:Done calling model_fn.\n",
      "INFO:tensorflow:Create CheckpointSaverHook.\n",
      "INFO:tensorflow:Graph was finalized.\n",
      "INFO:tensorflow:Running local_init_op.\n",
      "INFO:tensorflow:Done running local_init_op.\n",
      "INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 0...\n",
      "INFO:tensorflow:Saving checkpoints for 0 into C:\\Users\\priya\\AppData\\Local\\Temp\\tmp1u_1hrec\\model.ckpt.\n",
      "INFO:tensorflow:Calling checkpoint listeners after saving checkpoint 0...\n",
      "INFO:tensorflow:loss = 252.40402, step = 0\n",
      "INFO:tensorflow:global_step/sec: 117.785\n",
      "INFO:tensorflow:loss = 1.2882797, step = 100 (0.850 sec)\n",
      "INFO:tensorflow:global_step/sec: 145.908\n",
      "INFO:tensorflow:loss = 1.1470636, step = 200 (0.685 sec)\n",
      "INFO:tensorflow:global_step/sec: 169.105\n",
      "INFO:tensorflow:loss = 1.0615424, step = 300 (0.592 sec)\n",
      "INFO:tensorflow:global_step/sec: 158.63\n",
      "INFO:tensorflow:loss = 1.1518364, step = 400 (0.630 sec)\n",
      "INFO:tensorflow:global_step/sec: 165.128\n",
      "INFO:tensorflow:loss = 1.2076252, step = 500 (0.605 sec)\n",
      "INFO:tensorflow:global_step/sec: 135.098\n",
      "INFO:tensorflow:loss = 0.8571297, step = 600 (0.741 sec)\n",
      "INFO:tensorflow:global_step/sec: 133.864\n",
      "INFO:tensorflow:loss = 0.8823182, step = 700 (0.750 sec)\n",
      "INFO:tensorflow:global_step/sec: 174.377\n",
      "INFO:tensorflow:loss = 0.82683206, step = 800 (0.570 sec)\n",
      "INFO:tensorflow:global_step/sec: 168.82\n",
      "INFO:tensorflow:loss = 0.75795597, step = 900 (0.592 sec)\n",
      "INFO:tensorflow:global_step/sec: 170.388\n",
      "INFO:tensorflow:loss = 0.7843326, step = 1000 (0.587 sec)\n",
      "INFO:tensorflow:global_step/sec: 162.377\n",
      "INFO:tensorflow:loss = 0.73525155, step = 1100 (0.616 sec)\n",
      "INFO:tensorflow:global_step/sec: 156.358\n",
      "INFO:tensorflow:loss = 0.7277217, step = 1200 (0.641 sec)\n",
      "INFO:tensorflow:global_step/sec: 165.737\n",
      "INFO:tensorflow:loss = 0.6767479, step = 1300 (0.604 sec)\n",
      "INFO:tensorflow:global_step/sec: 165.319\n",
      "INFO:tensorflow:loss = 0.68980193, step = 1400 (0.603 sec)\n",
      "INFO:tensorflow:global_step/sec: 153.291\n",
      "INFO:tensorflow:loss = 0.61832225, step = 1500 (0.653 sec)\n",
      "INFO:tensorflow:global_step/sec: 172.181\n",
      "INFO:tensorflow:loss = 0.59666187, step = 1600 (0.580 sec)\n",
      "INFO:tensorflow:global_step/sec: 145.003\n",
      "INFO:tensorflow:loss = 0.57975924, step = 1700 (0.689 sec)\n",
      "INFO:tensorflow:global_step/sec: 163.69\n",
      "INFO:tensorflow:loss = 0.617642, step = 1800 (0.612 sec)\n",
      "INFO:tensorflow:global_step/sec: 163.669\n",
      "INFO:tensorflow:loss = 0.59543586, step = 1900 (0.613 sec)\n",
      "INFO:tensorflow:global_step/sec: 183.124\n",
      "INFO:tensorflow:loss = 0.56887466, step = 2000 (0.544 sec)\n",
      "INFO:tensorflow:global_step/sec: 193.624\n",
      "INFO:tensorflow:loss = 0.57537645, step = 2100 (0.515 sec)\n",
      "INFO:tensorflow:global_step/sec: 192.073\n",
      "INFO:tensorflow:loss = 0.5398751, step = 2200 (0.522 sec)\n",
      "INFO:tensorflow:global_step/sec: 185.617\n",
      "INFO:tensorflow:loss = 0.5454755, step = 2300 (0.539 sec)\n",
      "INFO:tensorflow:global_step/sec: 186.419\n",
      "INFO:tensorflow:loss = 0.5337466, step = 2400 (0.535 sec)\n",
      "INFO:tensorflow:global_step/sec: 177.865\n",
      "INFO:tensorflow:loss = 0.49379426, step = 2500 (0.562 sec)\n",
      "INFO:tensorflow:global_step/sec: 191.086\n",
      "INFO:tensorflow:loss = 0.5097028, step = 2600 (0.525 sec)\n",
      "INFO:tensorflow:global_step/sec: 192.087\n",
      "INFO:tensorflow:loss = 0.49885303, step = 2700 (0.519 sec)\n",
      "INFO:tensorflow:global_step/sec: 183.786\n",
      "INFO:tensorflow:loss = 0.48831114, step = 2800 (0.545 sec)\n",
      "INFO:tensorflow:global_step/sec: 172.021\n",
      "INFO:tensorflow:loss = 0.48948747, step = 2900 (0.582 sec)\n",
      "INFO:tensorflow:global_step/sec: 182.751\n",
      "INFO:tensorflow:loss = 0.4759693, step = 3000 (0.546 sec)\n",
      "INFO:tensorflow:global_step/sec: 187.162\n",
      "INFO:tensorflow:loss = 0.49551022, step = 3100 (0.533 sec)\n",
      "INFO:tensorflow:global_step/sec: 192.887\n",
      "INFO:tensorflow:loss = 0.48725784, step = 3200 (0.519 sec)\n",
      "INFO:tensorflow:global_step/sec: 184.936\n",
      "INFO:tensorflow:loss = 0.4638728, step = 3300 (0.541 sec)\n",
      "INFO:tensorflow:global_step/sec: 168.654\n",
      "INFO:tensorflow:loss = 0.45646596, step = 3400 (0.592 sec)\n",
      "INFO:tensorflow:global_step/sec: 159.731\n",
      "INFO:tensorflow:loss = 0.45356557, step = 3500 (0.628 sec)\n",
      "INFO:tensorflow:global_step/sec: 167.671\n",
      "INFO:tensorflow:loss = 0.45237023, step = 3600 (0.594 sec)\n",
      "INFO:tensorflow:global_step/sec: 158.863\n",
      "INFO:tensorflow:loss = 0.4302163, step = 3700 (0.630 sec)\n",
      "INFO:tensorflow:global_step/sec: 151.928\n",
      "INFO:tensorflow:loss = 0.42633983, step = 3800 (0.657 sec)\n",
      "INFO:tensorflow:global_step/sec: 187.506\n",
      "INFO:tensorflow:loss = 0.43868837, step = 3900 (0.533 sec)\n",
      "INFO:tensorflow:global_step/sec: 194.894\n",
      "INFO:tensorflow:loss = 0.42610872, step = 4000 (0.513 sec)\n",
      "INFO:tensorflow:global_step/sec: 179.941\n",
      "INFO:tensorflow:loss = 0.44035923, step = 4100 (0.557 sec)\n",
      "INFO:tensorflow:global_step/sec: 193.381\n",
      "INFO:tensorflow:loss = 0.4304794, step = 4200 (0.517 sec)\n",
      "INFO:tensorflow:global_step/sec: 179.013\n",
      "INFO:tensorflow:loss = 0.41257557, step = 4300 (0.558 sec)\n",
      "INFO:tensorflow:global_step/sec: 167.149\n",
      "INFO:tensorflow:loss = 0.42279723, step = 4400 (0.603 sec)\n",
      "INFO:tensorflow:global_step/sec: 169.56\n",
      "INFO:tensorflow:loss = 0.43375498, step = 4500 (0.586 sec)\n",
      "INFO:tensorflow:global_step/sec: 159.671\n",
      "INFO:tensorflow:loss = 0.41596758, step = 4600 (0.627 sec)\n",
      "INFO:tensorflow:global_step/sec: 173.921\n",
      "INFO:tensorflow:loss = 0.41596633, step = 4700 (0.574 sec)\n",
      "INFO:tensorflow:global_step/sec: 187.318\n",
      "INFO:tensorflow:loss = 0.42380327, step = 4800 (0.533 sec)\n",
      "INFO:tensorflow:global_step/sec: 194.292\n",
      "INFO:tensorflow:loss = 0.4052489, step = 4900 (0.515 sec)\n",
      "INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 5000...\n",
      "INFO:tensorflow:Saving checkpoints for 5000 into C:\\Users\\priya\\AppData\\Local\\Temp\\tmp1u_1hrec\\model.ckpt.\n",
      "INFO:tensorflow:Calling checkpoint listeners after saving checkpoint 5000...\n",
      "INFO:tensorflow:Loss for final step: 0.39014083.\n",
      "INFO:tensorflow:Calling model_fn.\n",
      "INFO:tensorflow:Done calling model_fn.\n",
      "INFO:tensorflow:Starting evaluation at 2022-02-09T19:53:59\n",
      "INFO:tensorflow:Graph was finalized.\n",
      "INFO:tensorflow:Restoring parameters from C:\\Users\\priya\\AppData\\Local\\Temp\\tmp1u_1hrec\\model.ckpt-5000\n",
      "INFO:tensorflow:Running local_init_op.\n",
      "INFO:tensorflow:Done running local_init_op.\n",
      "INFO:tensorflow:Inference Time : 0.32464s\n",
      "INFO:tensorflow:Finished evaluation at 2022-02-09-19:53:59\n",
      "INFO:tensorflow:Saving dict for global step 5000: accuracy = 0.85333335, average_loss = 0.3771075, global_step = 5000, loss = 0.3771075\n",
      "INFO:tensorflow:Saving 'checkpoint_path' summary for global step 5000: C:\\Users\\priya\\AppData\\Local\\Temp\\tmp1u_1hrec\\model.ckpt-5000\n",
      "\n",
      "Test set accuracy: 0.853\n",
      "\n"
     ]
    }
   ],
   "source": [
    "classifier.train(\n",
    "    input_fn=lambda: input_fn(dftrain, y_train, training=True),\n",
    "    steps=5000)\n",
    "# We include a lambda to avoid creating an inner function previously\n",
    "\n",
    "eval_result = classifier.evaluate(\n",
    "    input_fn=lambda: input_fn(dfeval, y_eval, training=False))\n",
    "\n",
    "print('\\nTest set accuracy: {accuracy:0.3f}\\n'.format(**eval_result))"
   ]
  }
 ],
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