Commit d290a4d480ef55e81697d73a84b06a02112fed7b
1 parent
d2466c6f1d
Exists in
main
added test_mpg, renamed test_mnist
Showing 3 changed files with 503 additions and 298 deletions Inline Diff
python-notebook/test_ml.ipynb
View file @
d290a4d
{ | 1 | File was deleted | ||
"cells": [ | 2 | |||
{ | 3 | |||
"cell_type": "code", | 4 | |||
"execution_count": 1, | 5 | |||
"metadata": {}, | 6 | |||
"outputs": [], | 7 | |||
"source": [ | 8 | |||
"from tensorflow.keras.models import Sequential\n", | 9 | |||
"from tensorflow.keras.layers import Dense, Activation\n", | 10 | |||
"from tensorflow.keras.utils import to_categorical\n", | 11 | |||
"from tensorflow.keras.datasets import mnist\n", | 12 | |||
"import numpy as np\n", | 13 | |||
"import matplotlib.pyplot as plt" | 14 | |||
] | 15 | |||
}, | 16 | |||
{ | 17 | |||
"cell_type": "code", | 18 | |||
"execution_count": 2, | 19 | |||
"metadata": {}, | 20 | |||
"outputs": [ | 21 | |||
{ | 22 | |||
"name": "stdout", | 23 | |||
"output_type": "stream", | 24 | |||
"text": [ | 25 | |||
"x_train.shape: (60000, 28, 28)\n", | 26 | |||
"y_train.shape: (60000,)\n", | 27 | |||
"x_test.shape: (10000, 28, 28)\n", | 28 | |||
"y_test.shape: (10000,)\n" | 29 | |||
] | 30 | |||
} | 31 | |||
], | 32 | |||
"source": [ | 33 | |||
"(x_train, y_train), (x_test, y_test) = mnist.load_data()\n", | 34 | |||
"print(\"x_train.shape:\", x_train.shape)\n", | 35 | |||
"print(\"y_train.shape:\", y_train.shape)\n", | 36 | |||
"print(\"x_test.shape:\", x_test.shape)\n", | 37 | |||
"print(\"y_test.shape:\", y_test.shape)" | 38 | |||
] | 39 | |||
}, | 40 | |||
{ | 41 | |||
"cell_type": "code", | 42 | |||
"execution_count": 3, | 43 | |||
"metadata": {}, | 44 | |||
"outputs": [ | 45 | |||
{ | 46 | |||
"name": "stdout", | 47 | |||
"output_type": "stream", | 48 | |||
"text": [ | 49 | |||
"X Training matrix shape: (60000, 784)\n", | 50 | |||
"X Testing matrix shape: (10000, 784)\n" | 51 | |||
] | 52 | |||
} | 53 | |||
], | 54 | |||
"source": [ | 55 | |||
"X_train = x_train.reshape(60000, 784)\n", | 56 | |||
"X_test = x_test.reshape(10000, 784)\n", | 57 | |||
"X_train = X_train.astype('float32')\n", | 58 | |||
"X_test = X_test.astype('float32')\n", | 59 | |||
"X_train /= 255\n", | 60 | |||
"X_test /= 255\n", | 61 | |||
"print(\"X Training matrix shape:\", X_train.shape)\n", | 62 | |||
"print(\"X Testing matrix shape:\", X_test.shape)" | 63 | |||
] | 64 | |||
}, | 65 | |||
{ | 66 | |||
"cell_type": "code", | 67 | |||
"execution_count": 4, | 68 | |||
"metadata": {}, | 69 | |||
"outputs": [ | 70 | |||
{ | 71 | |||
"name": "stdout", | 72 | |||
"output_type": "stream", | 73 | |||
"text": [ | 74 | |||
"Y Training matrix shape: (60000, 10)\n", | 75 | |||
"Y Testing matrix shape: (10000, 10)\n" | 76 | |||
] | 77 | |||
} | 78 | |||
], | 79 | |||
"source": [ | 80 | |||
"Y_train = to_categorical(y_train, 10)\n", | 81 | |||
"Y_test = to_categorical(y_test, 10)\n", | 82 | |||
"print(\"Y Training matrix shape:\", Y_train.shape)\n", | 83 | |||
"print(\"Y Testing matrix shape:\", Y_test.shape)" | 84 | |||
] | 85 | |||
}, | 86 | |||
{ | 87 | |||
"cell_type": "code", | 88 | |||
"execution_count": 5, | 89 | |||
"metadata": {}, | 90 | |||
"outputs": [ | 91 | |||
{ | 92 | |||
"name": "stdout", | 93 | |||
"output_type": "stream", | 94 | |||
"text": [ | 95 | |||
"Model: \"sequential\"\n", | 96 | |||
"_________________________________________________________________\n", | 97 | |||
" Layer (type) Output Shape Param # \n", | 98 | |||
"=================================================================\n", | 99 | |||
" dense (Dense) (None, 512) 401920 \n", | 100 | |||
" \n", | 101 | |||
" activation (Activation) (None, 512) 0 \n", | 102 | |||
" \n", | 103 | |||
" dense_1 (Dense) (None, 256) 131328 \n", | 104 | |||
" \n", | 105 | |||
" activation_1 (Activation) (None, 256) 0 \n", | 106 | |||
" \n", | 107 | |||
" dense_2 (Dense) (None, 10) 2570 \n", | 108 | |||
" \n", | 109 | |||
" activation_2 (Activation) (None, 10) 0 \n", | 110 | |||
" \n", | 111 | |||
"=================================================================\n", | 112 | |||
"Total params: 535,818\n", | 113 | |||
"Trainable params: 535,818\n", | 114 | |||
"Non-trainable params: 0\n", | 115 | |||
"_________________________________________________________________\n" | 116 | |||
] | 117 | |||
}, | 118 | |||
{ | 119 | |||
"name": "stderr", | 120 | |||
"output_type": "stream", | 121 | |||
"text": [ | 122 | |||
"2022-02-17 08:15:51.572224: I tensorflow/core/platform/cpu_feature_guard.cc:151] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA\n", | 123 | |||
"To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n" | 124 | |||
] | 125 | |||
} | 126 | |||
], | 127 | |||
"source": [ | 128 | |||
"model = Sequential()\n", | 129 | |||
"model.add(Dense(512, input_shape=(784,)))\n", | 130 | |||
"model.add(Activation('relu'))\n", | 131 | |||
"model.add(Dense(256))\n", | 132 | |||
"model.add(Activation('relu'))\n", | 133 | |||
"model.add(Dense(10))\n", | 134 | |||
"model.add(Activation('softmax'))\n", | 135 | |||
"model.summary()" | 136 | |||
] | 137 | |||
}, | 138 | |||
{ | 139 | |||
"cell_type": "code", | 140 | |||
"execution_count": 6, | 141 | |||
"metadata": {}, | 142 | |||
"outputs": [ | 143 | |||
{ | 144 | |||
"name": "stdout", | 145 | |||
"output_type": "stream", | 146 | |||
"text": [ | 147 | |||
"Epoch 1/10\n", | 148 | |||
"469/469 [==============================] - 2s 3ms/step - loss: 0.2282 - accuracy: 0.9332\n", | 149 | |||
"Epoch 2/10\n", | 150 | |||
"469/469 [==============================] - 2s 3ms/step - loss: 0.0823 - accuracy: 0.9749\n", | 151 | |||
"Epoch 3/10\n", | 152 | |||
"469/469 [==============================] - 2s 4ms/step - loss: 0.0515 - accuracy: 0.9841\n", | 153 | |||
"Epoch 4/10\n", | 154 | |||
"469/469 [==============================] - 2s 3ms/step - loss: 0.0365 - accuracy: 0.9884\n", | 155 | |||
"Epoch 5/10\n", | 156 | |||
"469/469 [==============================] - 2s 4ms/step - loss: 0.0278 - accuracy: 0.9912\n", | 157 | |||
"Epoch 6/10\n", | 158 | |||
"469/469 [==============================] - 2s 3ms/step - loss: 0.0223 - accuracy: 0.9924\n", | 159 | |||
"Epoch 7/10\n", | 160 | |||
"469/469 [==============================] - 2s 4ms/step - loss: 0.0176 - accuracy: 0.9942\n", | 161 | |||
"Epoch 8/10\n", | 162 | |||
"469/469 [==============================] - 2s 3ms/step - loss: 0.0164 - accuracy: 0.9944\n", | 163 | |||
"Epoch 9/10\n", | 164 | |||
"469/469 [==============================] - 2s 3ms/step - loss: 0.0142 - accuracy: 0.9949\n", | 165 | |||
"Epoch 10/10\n", | 166 | |||
"469/469 [==============================] - 2s 3ms/step - loss: 0.0097 - accuracy: 0.9969\n" | 167 | |||
] | 168 | |||
}, | 169 | |||
{ | 170 | |||
"data": { | 171 | |||
"text/plain": [ | 172 | |||
"<keras.callbacks.History at 0x7fefbc6d0750>" | 173 | |||
] | 174 | |||
}, | 175 | |||
"execution_count": 6, | 176 | |||
"metadata": {}, | 177 | |||
"output_type": "execute_result" | 178 | |||
} | 179 | |||
], | 180 | |||
"source": [ | 181 | |||
"model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])\n", | 182 | |||
"model.fit(X_train, Y_train, batch_size=128, epochs=10, verbose=1)" | 183 | |||
] | 184 | |||
}, | 185 | |||
{ | 186 | |||
"cell_type": "code", | 187 | |||
"execution_count": 7, | 188 | |||
"metadata": {}, | 189 | |||
"outputs": [ | 190 | |||
{ | 191 | |||
"name": "stdout", | 192 | |||
"output_type": "stream", | 193 | |||
"text": [ | 194 | |||
"313/313 [==============================] - 0s 1ms/step - loss: 0.0739 - accuracy: 0.9819\n", | 195 | |||
"Test score: 0.07394378632307053\n", | 196 | |||
"Test accuracy: 0.9818999767303467\n" | 197 | |||
] | 198 | |||
} | 199 | |||
], | 200 | |||
"source": [ | 201 | |||
"score = model.evaluate(X_test, Y_test)\n", | 202 | |||
"print('Test score:', score[0])\n", | 203 | |||
"print('Test accuracy:', score[1])" | 204 | |||
] | 205 | |||
}, | 206 | |||
{ | 207 | |||
"cell_type": "code", | 208 | |||
"execution_count": 8, | 209 | |||
"metadata": {}, | 210 | |||
"outputs": [], | 211 | |||
"source": [ | 212 | |||
"predicted_classes = np.argmax(model.predict(X_test), axis=1)\n", | 213 | |||
"correct_indices = np.nonzero(predicted_classes == y_test)[0]\n", | 214 | |||
"incorrect_indices = np.nonzero(predicted_classes != y_test)[0]" | 215 | |||
] | 216 | |||
}, | 217 | |||
{ | 218 | |||
"cell_type": "code", | 219 | |||
"execution_count": 13, | 220 | |||
"metadata": {}, | 221 | |||
"outputs": [ | 222 | |||
{ | 223 | |||
"data": { | 224 | |||
"image/png": "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", | 225 | |||
"text/plain": [ | 226 | |||
"<Figure size 432x288 with 8 Axes>" | 227 | |||
] | 228 | |||
}, | 229 | |||
"metadata": {}, | 230 | |||
"output_type": "display_data" | 231 | |||
} | 232 | |||
], | 233 | |||
"source": [ | 234 | |||
"ax = plt.figure()\n", | 235 | |||
"ax.patch.set_facecolor('white')\n", | 236 | |||
"for i in range(9):\n", | 237 | |||
" plt.subplot(3,3,i+1)\n", | 238 | |||
" correct = correct_indices[i]\n", | 239 | |||
" plt.imshow(X_test[correct].reshape(28, 28), cmap='gray')\n", | 240 | |||
" plt.title(\"Predicted {}, Class {}\".format(predicted_classes[correct], y_test[correct]))\n", | 241 | |||
" plt.tight_layout()" | 242 | |||
] | 243 | |||
}, | 244 | |||
{ | 245 | |||
"cell_type": "code", | 246 | |||
"execution_count": 14, | 247 | |||
"metadata": {}, | 248 | |||
"outputs": [ | 249 | |||
{ | 250 | |||
"data": { | 251 | |||
"image/png": "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", | 252 | |||
"text/plain": [ | 253 | |||
"<Figure size 432x288 with 8 Axes>" | 254 | |||
] | 255 | |||
}, | 256 | |||
"metadata": {}, | 257 | |||
"output_type": "display_data" | 258 | |||
} | 259 | |||
], | 260 | |||
"source": [ | 261 | |||
"ax = plt.figure()\n", | 262 | |||
"ax.patch.set_facecolor('white')\n", | 263 | |||
"for i in range(9):\n", | 264 | |||
" plt.subplot(3,3,i+1)\n", | 265 | |||
" incorrect = incorrect_indices[i]\n", | 266 | |||
" plt.imshow(X_test[incorrect].reshape(28, 28), cmap='gray')\n", | 267 | |||
" plt.title(\"Predicted {}, Class {}\".format(predicted_classes[incorrect], y_test[incorrect]))\n", | 268 | |||
" plt.tight_layout()" | 269 | |||
] | 270 | |||
} | 271 | |||
], | 272 | |||
"metadata": { | 273 | |||
"interpreter": { | 274 | |||
"hash": "80dbe1014b4652684caa329d41db00af3ae439be86b11eab7e35b518e5d8ab1a" | 275 | |||
}, | 276 | |||
"kernelspec": { | 277 | |||
"display_name": "Python 3.7.9 64-bit ('venv': venv)", | 278 | |||
"language": "python", | 279 | |||
"name": "python3" | 280 | |||
}, | 281 | |||
"language_info": { | 282 | |||
"codemirror_mode": { | 283 | |||
"name": "ipython", | 284 | |||
"version": 3 | 285 | |||
}, | 286 | |||
"file_extension": ".py", | 287 | |||
"mimetype": "text/x-python", | 288 | |||
"name": "python", | 289 | |||
"nbconvert_exporter": "python", | 290 | |||
"pygments_lexer": "ipython3", | 291 | |||
"version": "3.7.9" | 292 | |||
}, | 293 | |||
"orig_nbformat": 4 | 294 | |||
}, | 295 | |||
"nbformat": 4, | 296 | |||
"nbformat_minor": 2 | 297 | |||
} | 298 |
python-notebook/test_mnist.ipynb
View file @
d290a4d
File was created | 1 | { | ||
2 | "cells": [ | |||
3 | { | |||
4 | "cell_type": "code", | |||
5 | "execution_count": 1, | |||
6 | "metadata": {}, | |||
7 | "outputs": [], | |||
8 | "source": [ | |||
9 | "from tensorflow.keras.models import Sequential\n", | |||
10 | "from tensorflow.keras.layers import Dense, Activation\n", | |||
11 | "from tensorflow.keras.utils import to_categorical\n", | |||
12 | "from tensorflow.keras.datasets import mnist\n", | |||
13 | "import numpy as np\n", | |||
14 | "import matplotlib.pyplot as plt" | |||
15 | ] | |||
16 | }, | |||
17 | { | |||
18 | "cell_type": "code", | |||
19 | "execution_count": 2, | |||
20 | "metadata": {}, | |||
21 | "outputs": [ | |||
22 | { | |||
23 | "name": "stdout", | |||
24 | "output_type": "stream", | |||
25 | "text": [ | |||
26 | "x_train.shape: (60000, 28, 28)\n", | |||
27 | "y_train.shape: (60000,)\n", | |||
28 | "x_test.shape: (10000, 28, 28)\n", | |||
29 | "y_test.shape: (10000,)\n" | |||
30 | ] | |||
31 | } | |||
32 | ], | |||
33 | "source": [ | |||
34 | "(x_train, y_train), (x_test, y_test) = mnist.load_data()\n", | |||
35 | "print(\"x_train.shape:\", x_train.shape)\n", | |||
36 | "print(\"y_train.shape:\", y_train.shape)\n", | |||
37 | "print(\"x_test.shape:\", x_test.shape)\n", | |||
38 | "print(\"y_test.shape:\", y_test.shape)" | |||
39 | ] | |||
40 | }, | |||
41 | { | |||
42 | "cell_type": "code", | |||
43 | "execution_count": 3, | |||
44 | "metadata": {}, | |||
45 | "outputs": [ | |||
46 | { | |||
47 | "name": "stdout", | |||
48 | "output_type": "stream", | |||
49 | "text": [ | |||
50 | "X Training matrix shape: (60000, 784)\n", | |||
51 | "X Testing matrix shape: (10000, 784)\n" | |||
52 | ] | |||
53 | } | |||
54 | ], | |||
55 | "source": [ | |||
56 | "X_train = x_train.reshape(60000, 784)\n", | |||
57 | "X_test = x_test.reshape(10000, 784)\n", | |||
58 | "X_train = X_train.astype('float32')\n", | |||
59 | "X_test = X_test.astype('float32')\n", | |||
60 | "X_train /= 255\n", | |||
61 | "X_test /= 255\n", | |||
62 | "print(\"X Training matrix shape:\", X_train.shape)\n", | |||
63 | "print(\"X Testing matrix shape:\", X_test.shape)" | |||
64 | ] | |||
65 | }, | |||
66 | { | |||
67 | "cell_type": "code", | |||
68 | "execution_count": 4, | |||
69 | "metadata": {}, | |||
70 | "outputs": [ | |||
71 | { | |||
72 | "name": "stdout", | |||
73 | "output_type": "stream", | |||
74 | "text": [ | |||
75 | "Y Training matrix shape: (60000, 10)\n", | |||
76 | "Y Testing matrix shape: (10000, 10)\n" | |||
77 | ] | |||
78 | } | |||
79 | ], | |||
80 | "source": [ | |||
81 | "Y_train = to_categorical(y_train, 10)\n", | |||
82 | "Y_test = to_categorical(y_test, 10)\n", | |||
83 | "print(\"Y Training matrix shape:\", Y_train.shape)\n", | |||
84 | "print(\"Y Testing matrix shape:\", Y_test.shape)" | |||
85 | ] | |||
86 | }, | |||
87 | { | |||
88 | "cell_type": "code", | |||
89 | "execution_count": 26, | |||
90 | "metadata": {}, | |||
91 | "outputs": [ | |||
92 | { | |||
93 | "name": "stdout", | |||
94 | "output_type": "stream", | |||
95 | "text": [ | |||
96 | "Model: \"sequential_5\"\n", | |||
97 | "_________________________________________________________________\n", | |||
98 | " Layer (type) Output Shape Param # \n", | |||
99 | "=================================================================\n", | |||
100 | " dense_14 (Dense) (None, 10) 7850 \n", | |||
101 | " \n", | |||
102 | " dense_15 (Dense) (None, 10) 110 \n", | |||
103 | " \n", | |||
104 | "=================================================================\n", | |||
105 | "Total params: 7,960\n", | |||
106 | "Trainable params: 7,960\n", | |||
107 | "Non-trainable params: 0\n", | |||
108 | "_________________________________________________________________\n", | |||
109 | "Epoch 1/10\n", | |||
110 | "469/469 [==============================] - 1s 2ms/step - loss: 0.7754 - accuracy: 0.7699\n", | |||
111 | "Epoch 2/10\n", | |||
112 | "469/469 [==============================] - 1s 2ms/step - loss: 0.3596 - accuracy: 0.8988\n", | |||
113 | "Epoch 3/10\n", | |||
114 | "469/469 [==============================] - 1s 2ms/step - loss: 0.3038 - accuracy: 0.9142\n", | |||
115 | "Epoch 4/10\n", | |||
116 | "469/469 [==============================] - 1s 2ms/step - loss: 0.2782 - accuracy: 0.9214\n", | |||
117 | "Epoch 5/10\n", | |||
118 | "469/469 [==============================] - 1s 2ms/step - loss: 0.2628 - accuracy: 0.9265\n", | |||
119 | "Epoch 6/10\n", | |||
120 | "469/469 [==============================] - 1s 2ms/step - loss: 0.2522 - accuracy: 0.9291\n", | |||
121 | "Epoch 7/10\n", | |||
122 | "469/469 [==============================] - 1s 2ms/step - loss: 0.2446 - accuracy: 0.9311\n", | |||
123 | "Epoch 8/10\n", | |||
124 | "469/469 [==============================] - 1s 2ms/step - loss: 0.2390 - accuracy: 0.9321\n", | |||
125 | "Epoch 9/10\n", | |||
126 | "469/469 [==============================] - 1s 2ms/step - loss: 0.2348 - accuracy: 0.9333\n", | |||
127 | "Epoch 10/10\n", | |||
128 | "469/469 [==============================] - 1s 2ms/step - loss: 0.2301 - accuracy: 0.9351\n", | |||
129 | "313/313 [==============================] - 0s 1ms/step - loss: 0.2358 - accuracy: 0.9323\n", | |||
130 | "Test score: 0.23583918809890747\n", | |||
131 | "Test accuracy: 0.9322999715805054\n" | |||
132 | ] | |||
133 | } | |||
134 | ], | |||
135 | "source": [ | |||
136 | "model = Sequential(\n", | |||
137 | " [\n", | |||
138 | " Dense(10, activation='relu', input_shape=(784,)),\n", | |||
139 | " Dense(10, activation='softmax'),\n", | |||
140 | " ]\n", | |||
141 | ")\n", | |||
142 | "model.summary()\n", | |||
143 | "\n", | |||
144 | "model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])\n", | |||
145 | "model.fit(X_train, Y_train, batch_size=128, epochs=10, verbose=1)\n", | |||
146 | "\n", | |||
147 | "score = model.evaluate(X_test, Y_test)\n", | |||
148 | "print('Test score:', score[0])\n", | |||
149 | "print('Test accuracy:', score[1])" | |||
150 | ] | |||
151 | }, | |||
152 | { | |||
153 | "cell_type": "code", | |||
154 | "execution_count": 24, | |||
155 | "metadata": {}, | |||
156 | "outputs": [ | |||
157 | { | |||
158 | "data": { | |||
159 | "image/png": "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", | |||
160 | "text/plain": [ | |||
161 | "<Figure size 432x288 with 8 Axes>" | |||
162 | ] | |||
163 | }, | |||
164 | "metadata": {}, | |||
165 | "output_type": "display_data" | |||
166 | }, | |||
167 | { | |||
168 | "data": { | |||
169 | "image/png": "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", | |||
170 | "text/plain": [ | |||
171 | "<Figure size 432x288 with 8 Axes>" | |||
172 | ] | |||
173 | }, | |||
174 | "metadata": {}, | |||
175 | "output_type": "display_data" | |||
176 | } | |||
177 | ], | |||
178 | "source": [ | |||
179 | "predicted_classes = np.argmax(model.predict(X_test), axis=1)\n", | |||
180 | "correct_indices = np.nonzero(predicted_classes == y_test)[0]\n", | |||
181 | "incorrect_indices = np.nonzero(predicted_classes != y_test)[0]\n", | |||
182 | "\n", | |||
183 | "ax = plt.figure()\n", | |||
184 | "ax.patch.set_facecolor('white')\n", | |||
185 | "for i in range(9):\n", | |||
186 | " plt.subplot(3,3,i+1)\n", | |||
187 | " correct = correct_indices[i]\n", | |||
188 | " plt.imshow(X_test[correct].reshape(28, 28), cmap='gray')\n", | |||
189 | " plt.title(\"Predicted {}, Class {}\".format(predicted_classes[correct], y_test[correct]))\n", | |||
190 | " plt.tight_layout()\n", | |||
191 | "\n", | |||
192 | "ax = plt.figure()\n", | |||
193 | "ax.patch.set_facecolor('white')\n", | |||
194 | "for i in range(9):\n", | |||
195 | " plt.subplot(3,3,i+1)\n", | |||
196 | " incorrect = incorrect_indices[i]\n", | |||
197 | " plt.imshow(X_test[incorrect].reshape(28, 28), cmap='gray')\n", | |||
198 | " plt.title(\"Predicted {}, Class {}\".format(predicted_classes[incorrect], y_test[incorrect]))\n", | |||
199 | " plt.tight_layout()" | |||
200 | ] | |||
201 | } | |||
202 | ], | |||
203 | "metadata": { | |||
204 | "interpreter": { | |||
205 | "hash": "80dbe1014b4652684caa329d41db00af3ae439be86b11eab7e35b518e5d8ab1a" | |||
206 | }, | |||
207 | "kernelspec": { | |||
208 | "display_name": "Python 3.7.9 64-bit ('venv': venv)", | |||
209 | "language": "python", | |||
210 | "name": "python3" | |||
211 | }, | |||
212 | "language_info": { | |||
213 | "codemirror_mode": { | |||
214 | "name": "ipython", | |||
215 | "version": 3 | |||
216 | }, | |||
217 | "file_extension": ".py", | |||
218 | "mimetype": "text/x-python", | |||
219 | "name": "python", | |||
220 | "nbconvert_exporter": "python", | |||
221 | "pygments_lexer": "ipython3", | |||
222 | "version": "3.7.9" | |||
223 | }, | |||
224 | "orig_nbformat": 4 | |||
225 | }, | |||
226 | "nbformat": 4, | |||
227 | "nbformat_minor": 2 | |||
228 | } |
python-notebook/test_mpg.ipynb
View file @
d290a4d
File was created | 1 | { | ||
2 | "cells": [ | |||
3 | { | |||
4 | "cell_type": "code", | |||
5 | "execution_count": 1, | |||
6 | "metadata": {}, | |||
7 | "outputs": [ | |||
8 | { | |||
9 | "name": "stdout", | |||
10 | "output_type": "stream", | |||
11 | "text": [ | |||
12 | "2.7.0\n" | |||
13 | ] | |||
14 | } | |||
15 | ], | |||
16 | "source": [ | |||
17 | "import pathlib\n", | |||
18 | "\n", | |||
19 | "import matplotlib.pyplot as plt\n", | |||
20 | "import pandas as pd\n", | |||
21 | "import seaborn as sns\n", | |||
22 | "\n", | |||
23 | "import tensorflow as tf\n", | |||
24 | "from tensorflow import keras\n", | |||
25 | "from tensorflow.keras import layers\n", | |||
26 | "\n", | |||
27 | "print(tf.__version__)" | |||
28 | ] | |||
29 | }, | |||
30 | { | |||
31 | "cell_type": "code", | |||
32 | "execution_count": 2, | |||
33 | "metadata": {}, | |||
34 | "outputs": [ | |||
35 | { | |||
36 | "name": "stdout", | |||
37 | "output_type": "stream", | |||
38 | "text": [ | |||
39 | "Downloading data from http://archive.ics.uci.edu/ml/machine-learning-databases/auto-mpg/auto-mpg.data\n", | |||
40 | "32768/30286 [================================] - 0s 1us/step\n", | |||
41 | "40960/30286 [========================================] - 0s 1us/step\n" | |||
42 | ] | |||
43 | }, | |||
44 | { | |||
45 | "data": { | |||
46 | "text/plain": [ | |||
47 | "'/Users/ffee21/.keras/datasets/auto-mpg.data'" | |||
48 | ] | |||
49 | }, | |||
50 | "execution_count": 2, | |||
51 | "metadata": {}, | |||
52 | "output_type": "execute_result" | |||
53 | } | |||
54 | ], | |||
55 | "source": [ | |||
56 | "dataset_path = keras.utils.get_file(\"auto-mpg.data\", \"http://archive.ics.uci.edu/ml/machine-learning-databases/auto-mpg/auto-mpg.data\")\n", | |||
57 | "dataset_path" | |||
58 | ] | |||
59 | }, | |||
60 | { | |||
61 | "cell_type": "code", | |||
62 | "execution_count": 12, | |||
63 | "metadata": {}, | |||
64 | "outputs": [ | |||
65 | { | |||
66 | "data": { | |||
67 | "text/html": [ | |||
68 | "<div>\n", | |||
69 | "<style scoped>\n", | |||
70 | " .dataframe tbody tr th:only-of-type {\n", | |||
71 | " vertical-align: middle;\n", | |||
72 | " }\n", | |||
73 | "\n", | |||
74 | " .dataframe tbody tr th {\n", | |||
75 | " vertical-align: top;\n", | |||
76 | " }\n", | |||
77 | "\n", | |||
78 | " .dataframe thead th {\n", | |||
79 | " text-align: right;\n", | |||
80 | " }\n", | |||
81 | "</style>\n", | |||
82 | "<table border=\"1\" class=\"dataframe\">\n", | |||
83 | " <thead>\n", | |||
84 | " <tr style=\"text-align: right;\">\n", | |||
85 | " <th></th>\n", | |||
86 | " <th>MPG</th>\n", | |||
87 | " <th>Cylinders</th>\n", | |||
88 | " <th>Displacement</th>\n", | |||
89 | " <th>Horsepower</th>\n", | |||
90 | " <th>Weight</th>\n", | |||
91 | " <th>Acceleration</th>\n", | |||
92 | " <th>Model Year</th>\n", | |||
93 | " <th>USA</th>\n", | |||
94 | " <th>Europe</th>\n", | |||
95 | " <th>Japan</th>\n", | |||
96 | " </tr>\n", | |||
97 | " </thead>\n", | |||
98 | " <tbody>\n", | |||
99 | " <tr>\n", | |||
100 | " <th>393</th>\n", | |||
101 | " <td>27.0</td>\n", | |||
102 | " <td>4</td>\n", | |||
103 | " <td>140.0</td>\n", | |||
104 | " <td>86.0</td>\n", | |||
105 | " <td>2790.0</td>\n", | |||
106 | " <td>15.6</td>\n", | |||
107 | " <td>82</td>\n", | |||
108 | " <td>1.0</td>\n", | |||
109 | " <td>0.0</td>\n", | |||
110 | " <td>0.0</td>\n", | |||
111 | " </tr>\n", | |||
112 | " <tr>\n", | |||
113 | " <th>394</th>\n", | |||
114 | " <td>44.0</td>\n", | |||
115 | " <td>4</td>\n", | |||
116 | " <td>97.0</td>\n", | |||
117 | " <td>52.0</td>\n", | |||
118 | " <td>2130.0</td>\n", | |||
119 | " <td>24.6</td>\n", | |||
120 | " <td>82</td>\n", | |||
121 | " <td>0.0</td>\n", | |||
122 | " <td>1.0</td>\n", | |||
123 | " <td>0.0</td>\n", | |||
124 | " </tr>\n", | |||
125 | " <tr>\n", | |||
126 | " <th>395</th>\n", | |||
127 | " <td>32.0</td>\n", | |||
128 | " <td>4</td>\n", | |||
129 | " <td>135.0</td>\n", | |||
130 | " <td>84.0</td>\n", | |||
131 | " <td>2295.0</td>\n", | |||
132 | " <td>11.6</td>\n", | |||
133 | " <td>82</td>\n", | |||
134 | " <td>1.0</td>\n", | |||
135 | " <td>0.0</td>\n", | |||
136 | " <td>0.0</td>\n", | |||
137 | " </tr>\n", | |||
138 | " <tr>\n", | |||
139 | " <th>396</th>\n", | |||
140 | " <td>28.0</td>\n", | |||
141 | " <td>4</td>\n", | |||
142 | " <td>120.0</td>\n", | |||
143 | " <td>79.0</td>\n", | |||
144 | " <td>2625.0</td>\n", | |||
145 | " <td>18.6</td>\n", | |||
146 | " <td>82</td>\n", | |||
147 | " <td>1.0</td>\n", | |||
148 | " <td>0.0</td>\n", | |||
149 | " <td>0.0</td>\n", | |||
150 | " </tr>\n", | |||
151 | " <tr>\n", | |||
152 | " <th>397</th>\n", | |||
153 | " <td>31.0</td>\n", | |||
154 | " <td>4</td>\n", | |||
155 | " <td>119.0</td>\n", | |||
156 | " <td>82.0</td>\n", | |||
157 | " <td>2720.0</td>\n", | |||
158 | " <td>19.4</td>\n", | |||
159 | " <td>82</td>\n", | |||
160 | " <td>1.0</td>\n", | |||
161 | " <td>0.0</td>\n", | |||
162 | " <td>0.0</td>\n", | |||
163 | " </tr>\n", | |||
164 | " </tbody>\n", | |||
165 | "</table>\n", | |||
166 | "</div>" | |||
167 | ], | |||
168 | "text/plain": [ | |||
169 | " MPG Cylinders Displacement Horsepower Weight Acceleration \\\n", | |||
170 | "393 27.0 4 140.0 86.0 2790.0 15.6 \n", | |||
171 | "394 44.0 4 97.0 52.0 2130.0 24.6 \n", | |||
172 | "395 32.0 4 135.0 84.0 2295.0 11.6 \n", | |||
173 | "396 28.0 4 120.0 79.0 2625.0 18.6 \n", | |||
174 | "397 31.0 4 119.0 82.0 2720.0 19.4 \n", | |||
175 | "\n", | |||
176 | " Model Year USA Europe Japan \n", | |||
177 | "393 82 1.0 0.0 0.0 \n", | |||
178 | "394 82 0.0 1.0 0.0 \n", | |||
179 | "395 82 1.0 0.0 0.0 \n", | |||
180 | "396 82 1.0 0.0 0.0 \n", | |||
181 | "397 82 1.0 0.0 0.0 " | |||
182 | ] | |||
183 | }, | |||
184 | "execution_count": 12, | |||
185 | "metadata": {}, | |||
186 | "output_type": "execute_result" | |||
187 | } | |||
188 | ], | |||
189 | "source": [ | |||
190 | "column_names = ['MPG','Cylinders','Displacement','Horsepower','Weight',\n", | |||
191 | " 'Acceleration', 'Model Year', 'Origin']\n", | |||
192 | "raw_dataset = pd.read_csv(dataset_path, names=column_names,\n", | |||
193 | " na_values = \"?\", comment='\\t',\n", | |||
194 | " sep=\" \", skipinitialspace=True)\n", | |||
195 | "\n", | |||
196 | "dataset = raw_dataset.copy()\n", | |||
197 | "# dataset.tail()\n", | |||
198 | "# dataset.isna().sum()\n", | |||
199 | "dataset = dataset.dropna()\n", | |||
200 | "origin = dataset.pop('Origin')\n", | |||
201 | "dataset['USA'] = (origin == 1)*1.0\n", | |||
202 | "dataset['Europe'] = (origin == 2)*1.0\n", | |||
203 | "dataset['Japan'] = (origin == 3)*1.0\n", | |||
204 | "dataset.tail()" | |||
205 | ] | |||
206 | }, | |||
207 | { | |||
208 | "cell_type": "code", | |||
209 | "execution_count": 13, | |||
210 | "metadata": {}, | |||
211 | "outputs": [], | |||
212 | "source": [ | |||
213 | "train_dataset = dataset.sample(frac=0.8,random_state=0)\n", | |||
214 | "test_dataset = dataset.drop(train_dataset.index)" | |||
215 | ] | |||
216 | }, | |||
217 | { | |||
218 | "cell_type": "code", | |||
219 | "execution_count": 14, | |||
220 | "metadata": {}, | |||
221 | "outputs": [ | |||
222 | { | |||
223 | "data": { | |||
224 | "text/plain": [ | |||
225 | "<seaborn.axisgrid.PairGrid at 0x7feb4eef3f10>" | |||
226 | ] | |||
227 | }, | |||
228 | "execution_count": 14, | |||
229 | "metadata": {}, | |||
230 | "output_type": "execute_result" | |||
231 | }, | |||
232 | { | |||
233 | "data": { | |||
234 | "image/png": "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", | |||
235 | "text/plain": [ | |||
236 | "<Figure size 720x720 with 20 Axes>" | |||
237 | ] | |||
238 | }, | |||
239 | "metadata": { | |||
240 | "needs_background": "light" | |||
241 | }, | |||
242 | "output_type": "display_data" | |||
243 | } | |||
244 | ], | |||
245 | "source": [ | |||
246 | "sns.pairplot(train_dataset[[\"MPG\", \"Cylinders\", \"Displacement\", \"Weight\"]], diag_kind=\"kde\")" | |||
247 | ] | |||
248 | } | |||
249 | ], | |||
250 | "metadata": { | |||
251 | "interpreter": { | |||
252 | "hash": "80dbe1014b4652684caa329d41db00af3ae439be86b11eab7e35b518e5d8ab1a" | |||
253 | }, | |||
254 | "kernelspec": { | |||
255 | "display_name": "Python 3.7.9 64-bit ('venv': venv)", | |||
256 | "language": "python", | |||
257 | "name": "python3" | |||
258 | }, | |||
259 | "language_info": { | |||
260 | "codemirror_mode": { | |||
261 | "name": "ipython", | |||
262 | "version": 3 | |||
263 | }, | |||
264 | "file_extension": ".py", | |||
265 | "mimetype": "text/x-python", | |||
266 | "name": "python", | |||
267 | "nbconvert_exporter": "python", | |||
268 | "pygments_lexer": "ipython3", | |||
269 | "version": "3.7.9" | |||
270 | }, | |||
271 | "orig_nbformat": 4 | |||
272 | }, | |||
273 | "nbformat": 4, | |||
274 | "nbformat_minor": 2 | |||
275 | } |