This commit is contained in:
Tomasz Grzybowski 2022-05-23 15:41:22 +02:00
parent 2d0ff832a0
commit 5d7c672070

View File

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"cells": [
{
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@ -26,7 +26,7 @@
},
{
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"id": "70e3b6e3",
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"outputs": [
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"9360"
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@ -52,7 +52,7 @@
},
{
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"id": "44f404d6",
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"outputs": [
@ -62,7 +62,7 @@
"720"
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"execution_count": 62,
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@ -74,7 +74,7 @@
},
{
"cell_type": "code",
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"execution_count": 104,
"id": "c760402a",
"metadata": {},
"outputs": [
@ -84,7 +84,7 @@
"10080"
]
},
"execution_count": 63,
"execution_count": 104,
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}
@ -96,7 +96,7 @@
},
{
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@ -106,7 +106,7 @@
},
{
"cell_type": "code",
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"execution_count": 106,
"id": "91c047f6",
"metadata": {},
"outputs": [
@ -493,7 +493,7 @@
"[10080 rows x 73 columns]"
]
},
"execution_count": 65,
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@ -505,7 +505,7 @@
},
{
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@ -515,7 +515,7 @@
},
{
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"id": "e03bae07",
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"outputs": [
@ -902,7 +902,7 @@
"[9360 rows x 73 columns]"
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},
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@ -913,7 +913,7 @@
},
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},
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},
{
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@ -959,7 +959,7 @@
},
{
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@ -969,7 +969,7 @@
},
{
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"outputs": [
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"text": [
"(None, 73) <dtype: 'float32'>\n",
"(None, 1) <dtype: 'float32'>\n",
"dense_26 (None, 73) float32\n",
"dense_27 (None, 2048) float32\n",
"dense_28 (None, 1024) float32\n",
"dense_29 (None, 512) float32\n",
"dense_30 (None, 256) float32\n",
"dense_31 (None, 128) float32\n",
"dense_32 (None, 64) float32\n",
"dense_33 (None, 32) float32\n",
"dense_34 (None, 16) float32\n"
"dense_44 (None, 73) float32\n",
"dense_45 (None, 2048) float32\n",
"dense_46 (None, 1024) float32\n",
"dense_47 (None, 512) float32\n",
"dense_48 (None, 256) float32\n",
"dense_49 (None, 128) float32\n",
"dense_50 (None, 64) float32\n",
"dense_51 (None, 32) float32\n",
"dense_52 (None, 16) float32\n"
]
},
{
@ -996,7 +996,7 @@
"[None, None, None, None, None, None, None, None, None]"
]
},
"execution_count": 72,
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}
@ -1009,7 +1009,7 @@
},
{
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@ -1020,174 +1020,174 @@
"output_type": "stream",
"text": [
"Epoch 1/80\n",
"293/293 [==============================] - 6s 17ms/step - loss: 1134.1598 - mean_squared_error: 1134.1598\n",
"293/293 [==============================] - 5s 17ms/step - loss: 1108.6758 - mean_squared_error: 1108.6758\n",
"Epoch 2/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 714.3663 - mean_squared_error: 714.3663\n",
"293/293 [==============================] - 5s 17ms/step - loss: 671.0632 - mean_squared_error: 671.0632\n",
"Epoch 3/80\n",
"293/293 [==============================] - 5s 17ms/step - loss: 530.2103 - mean_squared_error: 530.2103\n",
"293/293 [==============================] - 5s 17ms/step - loss: 536.2025 - mean_squared_error: 536.2025\n",
"Epoch 4/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 466.3124 - mean_squared_error: 466.3124\n",
"293/293 [==============================] - 5s 16ms/step - loss: 457.3617 - mean_squared_error: 457.3617\n",
"Epoch 5/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 408.9340 - mean_squared_error: 408.9340\n",
"293/293 [==============================] - 5s 16ms/step - loss: 406.1862 - mean_squared_error: 406.1862\n",
"Epoch 6/80\n",
"293/293 [==============================] - 5s 17ms/step - loss: 376.8569 - mean_squared_error: 376.8569\n",
"293/293 [==============================] - 5s 17ms/step - loss: 369.4316 - mean_squared_error: 369.4316\n",
"Epoch 7/80\n",
"293/293 [==============================] - 5s 17ms/step - loss: 306.2373 - mean_squared_error: 306.2373\n",
"293/293 [==============================] - 5s 17ms/step - loss: 312.5139 - mean_squared_error: 312.5139\n",
"Epoch 8/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 265.6877 - mean_squared_error: 265.6877\n",
"293/293 [==============================] - 5s 17ms/step - loss: 270.2833 - mean_squared_error: 270.2833\n",
"Epoch 9/80\n",
"293/293 [==============================] - 5s 17ms/step - loss: 232.4935 - mean_squared_error: 232.4935\n",
"293/293 [==============================] - 5s 17ms/step - loss: 223.4037 - mean_squared_error: 223.4037\n",
"Epoch 10/80\n",
"293/293 [==============================] - 5s 18ms/step - loss: 190.4526 - mean_squared_error: 190.4526\n",
"293/293 [==============================] - 5s 17ms/step - loss: 179.4202 - mean_squared_error: 179.4202\n",
"Epoch 11/80\n",
"293/293 [==============================] - 5s 18ms/step - loss: 145.0189 - mean_squared_error: 145.0189\n",
"293/293 [==============================] - 5s 17ms/step - loss: 143.8777 - mean_squared_error: 143.8777\n",
"Epoch 12/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 119.3220 - mean_squared_error: 119.3220\n",
"293/293 [==============================] - 5s 18ms/step - loss: 135.4522 - mean_squared_error: 135.4522\n",
"Epoch 13/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 91.1009 - mean_squared_error: 91.1009\n",
"293/293 [==============================] - 5s 18ms/step - loss: 109.2838 - mean_squared_error: 109.2838\n",
"Epoch 14/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 74.9345 - mean_squared_error: 74.9345\n",
"293/293 [==============================] - 5s 17ms/step - loss: 88.6090 - mean_squared_error: 88.6090\n",
"Epoch 15/80\n",
"293/293 [==============================] - 5s 17ms/step - loss: 60.5697 - mean_squared_error: 60.5697\n",
"293/293 [==============================] - 5s 17ms/step - loss: 69.3139 - mean_squared_error: 69.3139\n",
"Epoch 16/80\n",
"293/293 [==============================] - 5s 18ms/step - loss: 60.6215 - mean_squared_error: 60.6215\n",
"293/293 [==============================] - 5s 16ms/step - loss: 67.1195 - mean_squared_error: 67.1195\n",
"Epoch 17/80\n",
"293/293 [==============================] - 5s 18ms/step - loss: 53.4988 - mean_squared_error: 53.4988\n",
"293/293 [==============================] - 5s 16ms/step - loss: 59.6054 - mean_squared_error: 59.6054\n",
"Epoch 18/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 46.9713 - mean_squared_error: 46.9713\n",
"293/293 [==============================] - 5s 17ms/step - loss: 50.4958 - mean_squared_error: 50.4958\n",
"Epoch 19/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 43.6367 - mean_squared_error: 43.6367\n",
"293/293 [==============================] - 5s 17ms/step - loss: 41.2413 - mean_squared_error: 41.2413\n",
"Epoch 20/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 43.7172 - mean_squared_error: 43.7172\n",
"293/293 [==============================] - 5s 17ms/step - loss: 35.0757 - mean_squared_error: 35.0757\n",
"Epoch 21/80\n",
"293/293 [==============================] - 5s 17ms/step - loss: 38.5771 - mean_squared_error: 38.5771\n",
"293/293 [==============================] - 5s 17ms/step - loss: 43.3807 - mean_squared_error: 43.3807\n",
"Epoch 22/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 39.4714 - mean_squared_error: 39.4714\n",
"293/293 [==============================] - 5s 17ms/step - loss: 48.1348 - mean_squared_error: 48.1348\n",
"Epoch 23/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 40.1202 - mean_squared_error: 40.1202\n",
"293/293 [==============================] - 5s 18ms/step - loss: 52.9108 - mean_squared_error: 52.9108\n",
"Epoch 24/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 53.1920 - mean_squared_error: 53.1920\n",
"293/293 [==============================] - 5s 17ms/step - loss: 40.8023 - mean_squared_error: 40.8023\n",
"Epoch 25/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 45.4968 - mean_squared_error: 45.4968\n",
"293/293 [==============================] - 5s 16ms/step - loss: 35.4987 - mean_squared_error: 35.4987\n",
"Epoch 26/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 34.6478 - mean_squared_error: 34.6478\n",
"293/293 [==============================] - 5s 16ms/step - loss: 35.0609 - mean_squared_error: 35.0609\n",
"Epoch 27/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 29.7110 - mean_squared_error: 29.7110\n",
"293/293 [==============================] - 5s 16ms/step - loss: 39.9937 - mean_squared_error: 39.9937\n",
"Epoch 28/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 24.7331 - mean_squared_error: 24.7331\n",
"293/293 [==============================] - 5s 17ms/step - loss: 29.5927 - mean_squared_error: 29.5927\n",
"Epoch 29/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 31.2403 - mean_squared_error: 31.2403\n",
"293/293 [==============================] - 5s 17ms/step - loss: 33.4916 - mean_squared_error: 33.4916\n",
"Epoch 30/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 28.0005 - mean_squared_error: 28.0005\n",
"293/293 [==============================] - 5s 17ms/step - loss: 37.4889 - mean_squared_error: 37.4889\n",
"Epoch 31/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 29.0533 - mean_squared_error: 29.0533\n",
"293/293 [==============================] - 5s 17ms/step - loss: 36.7416 - mean_squared_error: 36.7416\n",
"Epoch 32/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 30.9709 - mean_squared_error: 30.9709\n",
"293/293 [==============================] - 5s 16ms/step - loss: 34.1706 - mean_squared_error: 34.1706\n",
"Epoch 33/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 27.8636 - mean_squared_error: 27.8636\n",
"293/293 [==============================] - 5s 16ms/step - loss: 29.5588 - mean_squared_error: 29.5588\n",
"Epoch 34/80\n",
"293/293 [==============================] - 5s 17ms/step - loss: 38.6768 - mean_squared_error: 38.6768\n",
"293/293 [==============================] - 5s 16ms/step - loss: 35.8357 - mean_squared_error: 35.8357\n",
"Epoch 35/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 36.2994 - mean_squared_error: 36.2994\n",
"293/293 [==============================] - 5s 16ms/step - loss: 33.4907 - mean_squared_error: 33.4907\n",
"Epoch 36/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 32.9632 - mean_squared_error: 32.9632\n",
"293/293 [==============================] - 5s 16ms/step - loss: 26.6265 - mean_squared_error: 26.6265\n",
"Epoch 37/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 34.0196 - mean_squared_error: 34.0196\n",
"293/293 [==============================] - 5s 16ms/step - loss: 23.5669 - mean_squared_error: 23.5669\n",
"Epoch 38/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 27.4301 - mean_squared_error: 27.4301\n",
"293/293 [==============================] - 5s 16ms/step - loss: 20.1027 - mean_squared_error: 20.1027\n",
"Epoch 39/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 21.3594 - mean_squared_error: 21.3594\n",
"293/293 [==============================] - 5s 16ms/step - loss: 19.0630 - mean_squared_error: 19.0630\n",
"Epoch 40/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 15.9413 - mean_squared_error: 15.9413\n",
"293/293 [==============================] - 5s 16ms/step - loss: 22.2653 - mean_squared_error: 22.2653\n",
"Epoch 41/80\n",
"293/293 [==============================] - 5s 17ms/step - loss: 21.4223 - mean_squared_error: 21.4223\n",
"293/293 [==============================] - 5s 16ms/step - loss: 28.3499 - mean_squared_error: 28.3499\n",
"Epoch 42/80\n",
"293/293 [==============================] - 5s 17ms/step - loss: 24.0689 - mean_squared_error: 24.0689\n",
"293/293 [==============================] - 5s 16ms/step - loss: 30.2943 - mean_squared_error: 30.2943\n",
"Epoch 43/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 21.8016 - mean_squared_error: 21.8016\n",
"293/293 [==============================] - 5s 16ms/step - loss: 30.8464 - mean_squared_error: 30.8464\n",
"Epoch 44/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 22.8678 - mean_squared_error: 22.8678\n",
"293/293 [==============================] - 5s 18ms/step - loss: 25.8581 - mean_squared_error: 25.8581\n",
"Epoch 45/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 19.4661 - mean_squared_error: 19.4661\n",
"293/293 [==============================] - 5s 17ms/step - loss: 22.0973 - mean_squared_error: 22.0973\n",
"Epoch 46/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 21.0602 - mean_squared_error: 21.0602\n",
"293/293 [==============================] - 5s 17ms/step - loss: 20.3286 - mean_squared_error: 20.3286\n",
"Epoch 47/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 21.4916 - mean_squared_error: 21.4916\n",
"293/293 [==============================] - 5s 16ms/step - loss: 20.7386 - mean_squared_error: 20.7386\n",
"Epoch 48/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 24.5567 - mean_squared_error: 24.5567\n",
"293/293 [==============================] - 5s 16ms/step - loss: 20.1520 - mean_squared_error: 20.1520\n",
"Epoch 49/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 23.9477 - mean_squared_error: 23.9477\n",
"293/293 [==============================] - 5s 16ms/step - loss: 21.0666 - mean_squared_error: 21.0666\n",
"Epoch 50/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 21.6010 - mean_squared_error: 21.6010\n",
"293/293 [==============================] - 5s 16ms/step - loss: 20.2202 - mean_squared_error: 20.2202\n",
"Epoch 51/80\n",
"293/293 [==============================] - 5s 18ms/step - loss: 19.9157 - mean_squared_error: 19.9157\n",
"293/293 [==============================] - 5s 16ms/step - loss: 20.7954 - mean_squared_error: 20.7954\n",
"Epoch 52/80\n",
"293/293 [==============================] - 6s 19ms/step - loss: 21.2413 - mean_squared_error: 21.2413\n",
"293/293 [==============================] - 5s 16ms/step - loss: 16.0701 - mean_squared_error: 16.0701\n",
"Epoch 53/80\n",
"293/293 [==============================] - 6s 19ms/step - loss: 23.5774 - mean_squared_error: 23.5774\n",
"293/293 [==============================] - 5s 16ms/step - loss: 16.0172 - mean_squared_error: 16.0172\n",
"Epoch 54/80\n",
"293/293 [==============================] - 5s 17ms/step - loss: 20.9708 - mean_squared_error: 20.9708\n",
"293/293 [==============================] - 5s 16ms/step - loss: 16.2924 - mean_squared_error: 16.2924\n",
"Epoch 55/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 16.7699 - mean_squared_error: 16.7699\n",
"293/293 [==============================] - 5s 16ms/step - loss: 16.6287 - mean_squared_error: 16.6287\n",
"Epoch 56/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 11.5884 - mean_squared_error: 11.5884\n",
"293/293 [==============================] - 5s 16ms/step - loss: 16.3168 - mean_squared_error: 16.3168\n",
"Epoch 57/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 11.2608 - mean_squared_error: 11.2608\n",
"293/293 [==============================] - 5s 16ms/step - loss: 18.8847 - mean_squared_error: 18.8847\n",
"Epoch 58/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 13.6555 - mean_squared_error: 13.6555\n",
"293/293 [==============================] - 5s 16ms/step - loss: 20.1943 - mean_squared_error: 20.1943\n",
"Epoch 59/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 16.4050 - mean_squared_error: 16.4050\n",
"293/293 [==============================] - 5s 16ms/step - loss: 22.6101 - mean_squared_error: 22.6101\n",
"Epoch 60/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 23.0564 - mean_squared_error: 23.0564\n",
"293/293 [==============================] - 5s 16ms/step - loss: 19.8736 - mean_squared_error: 19.8736\n",
"Epoch 61/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 28.0808 - mean_squared_error: 28.0808\n",
"293/293 [==============================] - 5s 16ms/step - loss: 19.8947 - mean_squared_error: 19.8947\n",
"Epoch 62/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 19.2690 - mean_squared_error: 19.2690\n",
"293/293 [==============================] - 5s 16ms/step - loss: 19.0540 - mean_squared_error: 19.0540\n",
"Epoch 63/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 14.3920 - mean_squared_error: 14.3920\n",
"293/293 [==============================] - 5s 16ms/step - loss: 18.1842 - mean_squared_error: 18.1842\n",
"Epoch 64/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 12.5167 - mean_squared_error: 12.5167\n",
"293/293 [==============================] - 5s 16ms/step - loss: 15.4725 - mean_squared_error: 15.4725\n",
"Epoch 65/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 14.2031 - mean_squared_error: 14.2031\n",
"293/293 [==============================] - 5s 16ms/step - loss: 16.2298 - mean_squared_error: 16.2298\n",
"Epoch 66/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 13.2670 - mean_squared_error: 13.2670\n",
"293/293 [==============================] - 5s 16ms/step - loss: 13.2303 - mean_squared_error: 13.2303\n",
"Epoch 67/80\n",
"293/293 [==============================] - 5s 17ms/step - loss: 15.0297 - mean_squared_error: 15.0297\n",
"293/293 [==============================] - 5s 16ms/step - loss: 14.2212 - mean_squared_error: 14.2212\n",
"Epoch 68/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 16.3161 - mean_squared_error: 16.3161\n",
"293/293 [==============================] - 5s 16ms/step - loss: 12.7895 - mean_squared_error: 12.7895\n",
"Epoch 69/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 14.6367 - mean_squared_error: 14.6367\n",
"293/293 [==============================] - 5s 18ms/step - loss: 15.7551 - mean_squared_error: 15.7551\n",
"Epoch 70/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 12.4564 - mean_squared_error: 12.4564\n",
"293/293 [==============================] - 5s 17ms/step - loss: 18.4030 - mean_squared_error: 18.4030\n",
"Epoch 71/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 11.4511 - mean_squared_error: 11.4511\n",
"293/293 [==============================] - 5s 16ms/step - loss: 16.0214 - mean_squared_error: 16.0214\n",
"Epoch 72/80\n",
"293/293 [==============================] - 5s 17ms/step - loss: 14.1012 - mean_squared_error: 14.1012\n",
"293/293 [==============================] - 5s 17ms/step - loss: 12.3694 - mean_squared_error: 12.3694\n",
"Epoch 73/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 15.6135 - mean_squared_error: 15.6135\n",
"293/293 [==============================] - 5s 17ms/step - loss: 10.5107 - mean_squared_error: 10.5107\n",
"Epoch 74/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 16.4932 - mean_squared_error: 16.4932\n",
"293/293 [==============================] - 5s 17ms/step - loss: 11.7746 - mean_squared_error: 11.7746\n",
"Epoch 75/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 12.8654 - mean_squared_error: 12.8654\n",
"293/293 [==============================] - 5s 16ms/step - loss: 11.6589 - mean_squared_error: 11.6589\n",
"Epoch 76/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 10.6150 - mean_squared_error: 10.6150\n",
"293/293 [==============================] - 5s 16ms/step - loss: 14.1691 - mean_squared_error: 14.1691\n",
"Epoch 77/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 11.0828 - mean_squared_error: 11.0828\n",
"293/293 [==============================] - 5s 16ms/step - loss: 15.9365 - mean_squared_error: 15.9365\n",
"Epoch 78/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 12.4208 - mean_squared_error: 12.4208\n",
"293/293 [==============================] - 5s 17ms/step - loss: 15.4616 - mean_squared_error: 15.4616\n",
"Epoch 79/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 13.5073 - mean_squared_error: 13.5073\n",
"293/293 [==============================] - 5s 17ms/step - loss: 13.2958 - mean_squared_error: 13.2958\n",
"Epoch 80/80\n",
"293/293 [==============================] - 5s 16ms/step - loss: 13.8812 - mean_squared_error: 13.8812\n"
"293/293 [==============================] - 5s 17ms/step - loss: 11.3826 - mean_squared_error: 11.3826\n"
]
},
{
"data": {
"text/plain": [
"<keras.callbacks.History at 0x1b6116d01c0>"
"<keras.callbacks.History at 0x1b61bab69d0>"
]
},
"execution_count": 73,
"execution_count": 114,
"metadata": {},
"output_type": "execute_result"
}
@ -1199,7 +1199,7 @@
},
{
"cell_type": "code",
"execution_count": 74,
"execution_count": 115,
"id": "bad4d35a",
"metadata": {},
"outputs": [],
@ -1207,22 +1207,25 @@
"x_test = pd.read_csv('test-A/in.tsv', sep='\\t', names=in_columns)\n",
"#y_test = pd.read_csv('test-A/expected.tsv', sep='\\t',names=['rainfall'])\n",
"#x_test = x_test.drop(['nazwa_stacji', 'typ_zbioru'],axis=1)\n",
"df_train = pd.read_csv('train/in.tsv', names=in_columns, sep='\\t')"
"#df_train = pd.read_csv('train/in.tsv', names=in_columns, sep='\\t')\n",
"df_train = pd.read_csv('train/in.tsv', names=in_columns, sep='\\t')\n",
"df2_train = pd.read_csv('dev-0/in.tsv', names=in_columns, sep='\\t')\n",
"df_train = pd.concat([df_train, df2_train])"
]
},
{
"cell_type": "code",
"execution_count": 75,
"execution_count": 116,
"id": "a3b6fff0",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"9480"
"10080"
]
},
"execution_count": 75,
"execution_count": 116,
"metadata": {},
"output_type": "execute_result"
}
@ -1234,17 +1237,17 @@
},
{
"cell_type": "code",
"execution_count": 76,
"execution_count": 117,
"id": "cdf89362",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"9480"
"10080"
]
},
"execution_count": 76,
"execution_count": 117,
"metadata": {},
"output_type": "execute_result"
}
@ -1256,7 +1259,7 @@
},
{
"cell_type": "code",
"execution_count": 77,
"execution_count": 118,
"id": "fe00b876",
"metadata": {},
"outputs": [
@ -1450,7 +1453,7 @@
" <td>...</td>\n",
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"<p>9480 rows × 73 columns</p>\n",
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"</div>"
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@ -1581,12 +1584,12 @@
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@ -1620,12 +1623,12 @@
"2 0 ... 1 0 0 0 \n",
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"599 0 ... 0 0 0 0 \n",
"\n",
" miesiąc_7 miesiąc_8 miesiąc_9 miesiąc_10 miesiąc_11 miesiąc_12 \n",
"0 0 0 0 0 0 0 \n",
@ -1633,17 +1636,17 @@
"2 0 0 0 0 0 0 \n",
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"8759 0 0 0 0 0 1 \n",
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"598 0 0 0 0 1 0 \n",
"599 0 0 0 0 0 1 \n",
"\n",
"[9480 rows x 73 columns]"
"[10080 rows x 73 columns]"
]
},
"execution_count": 77,
"execution_count": 118,
"metadata": {},
"output_type": "execute_result"
}
@ -1655,7 +1658,7 @@
},
{
"cell_type": "code",
"execution_count": 78,
"execution_count": 119,
"id": "657a7976",
"metadata": {},
"outputs": [
@ -1849,7 +1852,7 @@
" <td>...</td>\n",
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@ -1873,7 +1876,7 @@
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@ -1897,7 +1900,7 @@
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@ -1921,7 +1924,7 @@
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@ -1945,7 +1948,7 @@
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@ -1970,7 +1973,7 @@
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>120 rows × 73 columns</p>\n",
"<p>720 rows × 73 columns</p>\n",
"</div>"
],
"text/plain": [
@ -1981,11 +1984,11 @@
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" id_stacji_249200490 id_stacji_249220150 id_stacji_249220180 \\\n",
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@ -1994,11 +1997,11 @@
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@ -2007,11 +2010,11 @@
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"717 0 0 0 \n",
"718 0 0 0 \n",
"719 0 0 0 \n",
"\n",
" id_stacji_251170090 ... miesiąc_3 miesiąc_4 miesiąc_5 miesiąc_6 \\\n",
"0 0 ... 0 0 0 0 \n",
@ -2020,11 +2023,11 @@
"3 0 ... 0 1 0 0 \n",
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".. ... ... ... ... ... ... \n",
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"718 0 ... 0 0 0 0 \n",
"719 0 ... 0 0 0 0 \n",
"\n",
" miesiąc_7 miesiąc_8 miesiąc_9 miesiąc_10 miesiąc_11 miesiąc_12 \n",
"0 0 0 0 0 0 0 \n",
@ -2033,16 +2036,16 @@
"3 0 0 0 0 0 0 \n",
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"119 0 0 0 0 0 1 \n",
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"716 0 0 1 0 0 0 \n",
"717 0 0 0 1 0 0 \n",
"718 0 0 0 0 1 0 \n",
"719 0 0 0 0 0 1 \n",
"\n",
"[120 rows x 73 columns]"
"[720 rows x 73 columns]"
]
},
"execution_count": 78,
"execution_count": 119,
"metadata": {},
"output_type": "execute_result"
}
@ -2054,7 +2057,7 @@
},
{
"cell_type": "code",
"execution_count": 79,
"execution_count": 120,
"id": "1163c550",
"metadata": {},
"outputs": [
@ -2062,7 +2065,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"4/4 [==============================] - 0s 3ms/step\n"
"23/23 [==============================] - 0s 4ms/step\n"
]
}
],
@ -2072,7 +2075,7 @@
},
{
"cell_type": "code",
"execution_count": 80,
"execution_count": 121,
"id": "6c24ee76",
"metadata": {},
"outputs": [
@ -2080,7 +2083,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"4/4 [==============================] - 0s 3ms/step\n"
"23/23 [==============================] - 0s 4ms/step\n"
]
}
],