final run of notebook

cyclical-features/Testing Cyclical Encoding.ipynb

@@ -38,7 +38,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 72,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [
     {
@@ -67,7 +67,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 73,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -140,7 +140,7 @@
        "2016-09-18 05:00:00    56.592497  1.922459"
       ]
      },
-     "execution_count": 73,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -159,7 +159,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 74,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -168,7 +168,7 @@
        "'temp-plot.html'"
       ]
      },
-     "execution_count": 74,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -201,7 +201,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 75,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -265,7 +265,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 76,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -290,7 +290,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 77,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -421,7 +421,7 @@
        "2016-09-18 05:00:00        -0.212947  "
       ]
      },
-     "execution_count": 77,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -433,7 +433,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 78,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -564,7 +564,7 @@
        "2014-01-01 06:15:00         0.999853  "
       ]
      },
-     "execution_count": 78,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -577,7 +577,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 79,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -586,7 +586,7 @@
        "'temp-plot.html'"
       ]
      },
-     "execution_count": 79,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -598,7 +598,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 80,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -607,7 +607,7 @@
        "'temp-plot.html'"
       ]
      },
-     "execution_count": 80,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -632,7 +632,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -733,9 +733,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 81,
+   "execution_count": 11,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/williamkoehrsen/.local/share/virtualenvs/insight-engine-JU9-2WuC/lib/python3.7/site-packages/sklearn/linear_model/base.py:485: RuntimeWarning:\n",
+      "\n",
+      "internal gelsd driver lwork query error, required iwork dimension not returned. This is likely the result of LAPACK bug 0038, fixed in LAPACK 3.2.2 (released July 21, 2010). Falling back to 'gelss' driver.\n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "from sklearn.linear_model import LinearRegression\n",
     "from sklearn.ensemble import RandomForestRegressor\n",
@@ -751,7 +762,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 82,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -838,7 +849,7 @@
        "2014-01-05 01:00:00   0.400667  0.390858  LinearRegression  cyclical"
       ]
      },
-     "execution_count": 82,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -849,7 +860,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 83,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -934,7 +945,7 @@
        "max         1.389055       0.958976"
       ]
      },
-     "execution_count": 83,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -954,7 +965,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 85,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -989,9 +1000,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "cd96ee33cbc84e7daed4fa3aeb769821",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "HBox(children=(IntProgress(value=0, description='Buildings', max=40, style=ProgressStyle(description_width='in…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "run_all_buildings(building_data_files)"
    ]
@@ -1007,7 +1040,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 86,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -1016,7 +1049,7 @@
        "40"
       ]
      },
-     "execution_count": 86,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1035,7 +1068,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 87,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1064,7 +1097,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 89,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -1129,7 +1162,7 @@
        "         RandomForestRegressor                       18.747120"
       ]
      },
-     "execution_count": 89,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1160,7 +1193,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 90,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1202,7 +1235,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 91,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1215,7 +1248,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 92,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
@@ -1294,7 +1327,7 @@
        "0  cyclical       LinearRegression                       29.121338          15"
       ]
      },
-     "execution_count": 92,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -1371,7 +1404,7 @@
        "max                        451.598475"
       ]
      },
-     "execution_count": 92,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1392,7 +1425,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 93,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
@@ -1525,7 +1558,7 @@
        "         RandomForestRegressor  48.092324  386.051141  "
       ]
      },
-     "execution_count": 93,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1543,7 +1576,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 95,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
@@ -1637,7 +1670,7 @@
        "RandomForestRegressor -0.358428  0.096175  0.255632  16.377598  "
       ]
      },
-     "execution_count": 95,
+     "execution_count": 23,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1683,7 +1716,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 96,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1693,7 +1726,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 97,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1728,7 +1761,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 98,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [
     {
@@ -1737,7 +1770,7 @@
        "'validation_results/all_scores.html'"
       ]
      },
-     "execution_count": 98,
+     "execution_count": 26,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -1747,7 +1780,7 @@
        "'validation_results/diff_in_scores.html'"
       ]
      },
-     "execution_count": 98,
+     "execution_count": 26,
      "metadata": {},
      "output_type": "execute_result"
     }

cyclical-features/validation_results/all_metrics.csv

@@ -1,3 +1,3 @@
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