diff --git a/.gitignore b/.gitignore
index f870c03..b67d97a 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,2 +1,3 @@
.ipynb_checkpoints
*/.ipynb_checkpoints
+Untitled.ipynb
diff --git a/data/X_engineered.csv b/data/X_engineered.csv
new file mode 100644
index 0000000..c2181b7
--- /dev/null
+++ b/data/X_engineered.csv
@@ -0,0 +1,398 @@
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diff --git a/data/X_straight.csv b/data/X_straight.csv
new file mode 100644
index 0000000..e574bb4
--- /dev/null
+++ b/data/X_straight.csv
@@ -0,0 +1,398 @@
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diff --git a/eda.ipynb b/eda.ipynb
index f0c4669..3d64be6 100644
--- a/eda.ipynb
+++ b/eda.ipynb
@@ -30,11 +30,11 @@
"id": "5ffa8b01-0b17-4ad8-8e85-f2656da50c9e",
"metadata": {
"execution": {
- "iopub.execute_input": "2022-08-01T04:20:10.964571Z",
- "iopub.status.busy": "2022-08-01T04:20:10.964037Z",
- "iopub.status.idle": "2022-08-01T04:20:11.911635Z",
- "shell.execute_reply": "2022-08-01T04:20:11.911048Z",
- "shell.execute_reply.started": "2022-08-01T04:20:10.964486Z"
+ "iopub.execute_input": "2022-08-01T14:48:44.692975Z",
+ "iopub.status.busy": "2022-08-01T14:48:44.692461Z",
+ "iopub.status.idle": "2022-08-01T14:48:46.367116Z",
+ "shell.execute_reply": "2022-08-01T14:48:46.366301Z",
+ "shell.execute_reply.started": "2022-08-01T14:48:44.692899Z"
},
"tags": []
},
@@ -107,11 +107,11 @@
"id": "3e633f5f-8a7f-4776-a855-f22fcb87e88d",
"metadata": {
"execution": {
- "iopub.execute_input": "2022-08-01T04:20:11.913047Z",
- "iopub.status.busy": "2022-08-01T04:20:11.912844Z",
- "iopub.status.idle": "2022-08-01T04:20:11.923117Z",
- "shell.execute_reply": "2022-08-01T04:20:11.922526Z",
- "shell.execute_reply.started": "2022-08-01T04:20:11.913032Z"
+ "iopub.execute_input": "2022-08-01T14:48:46.370085Z",
+ "iopub.status.busy": "2022-08-01T14:48:46.369414Z",
+ "iopub.status.idle": "2022-08-01T14:48:48.721115Z",
+ "shell.execute_reply": "2022-08-01T14:48:48.720341Z",
+ "shell.execute_reply.started": "2022-08-01T14:48:46.370055Z"
},
"tags": []
},
@@ -168,11 +168,11 @@
"id": "7342da99-d04a-4f4f-ad3c-06840144ec48",
"metadata": {
"execution": {
- "iopub.execute_input": "2022-08-01T04:20:11.924056Z",
- "iopub.status.busy": "2022-08-01T04:20:11.923876Z",
- "iopub.status.idle": "2022-08-01T04:20:11.935974Z",
- "shell.execute_reply": "2022-08-01T04:20:11.935279Z",
- "shell.execute_reply.started": "2022-08-01T04:20:11.924034Z"
+ "iopub.execute_input": "2022-08-01T14:48:48.722950Z",
+ "iopub.status.busy": "2022-08-01T14:48:48.722336Z",
+ "iopub.status.idle": "2022-08-01T14:48:48.731736Z",
+ "shell.execute_reply": "2022-08-01T14:48:48.730917Z",
+ "shell.execute_reply.started": "2022-08-01T14:48:48.722919Z"
},
"tags": []
},
@@ -182,8 +182,7 @@
"new_features['efficiency'] = df.horsepower / df.displacement\n",
"new_features['load'] = df.displacement / df.weight\n",
"new_features['bore_size'] = df.displacement / df.cylinders\n",
- "new_features['grunt'] = new_features.bore_size * new_features.efficiency * df.horsepower\n",
- "# new_features['grunt'] = (df.horsepower / new_features.bore_size) * new_features.efficiency"
+ "new_features['grunt'] = (df.horsepower / new_features.bore_size) * new_features.efficiency"
]
},
{
@@ -192,11 +191,11 @@
"id": "9fa0bf3e-d45b-4698-afac-e549db0de148",
"metadata": {
"execution": {
- "iopub.execute_input": "2022-08-01T04:20:11.936853Z",
- "iopub.status.busy": "2022-08-01T04:20:11.936679Z",
- "iopub.status.idle": "2022-08-01T04:20:12.329795Z",
- "shell.execute_reply": "2022-08-01T04:20:12.329065Z",
- "shell.execute_reply.started": "2022-08-01T04:20:11.936838Z"
+ "iopub.execute_input": "2022-08-01T14:48:48.733546Z",
+ "iopub.status.busy": "2022-08-01T14:48:48.732929Z",
+ "iopub.status.idle": "2022-08-01T14:48:51.073977Z",
+ "shell.execute_reply": "2022-08-01T14:48:51.073212Z",
+ "shell.execute_reply.started": "2022-08-01T14:48:48.733511Z"
},
"tags": []
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@@ -255,11 +254,11 @@
"id": "89cea145-4b6e-457b-9970-578144c1c364",
"metadata": {
"execution": {
- "iopub.execute_input": "2022-08-01T04:20:12.331981Z",
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- "shell.execute_reply": "2022-08-01T04:20:12.337017Z",
- "shell.execute_reply.started": "2022-08-01T04:20:12.331935Z"
+ "iopub.execute_input": "2022-08-01T14:48:51.075722Z",
+ "iopub.status.busy": "2022-08-01T14:48:51.075128Z",
+ "iopub.status.idle": "2022-08-01T14:48:51.082116Z",
+ "shell.execute_reply": "2022-08-01T14:48:51.081046Z",
+ "shell.execute_reply.started": "2022-08-01T14:48:51.075693Z"
},
"tags": []
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@@ -293,11 +292,11 @@
"id": "dbbfdab6-1cca-4329-a2ae-9258678ab0b1",
"metadata": {
"execution": {
- "iopub.execute_input": "2022-08-01T04:20:12.339782Z",
- "iopub.status.busy": "2022-08-01T04:20:12.339317Z",
- "iopub.status.idle": "2022-08-01T04:20:12.367167Z",
- "shell.execute_reply": "2022-08-01T04:20:12.365967Z",
- "shell.execute_reply.started": "2022-08-01T04:20:12.339751Z"
+ "iopub.execute_input": "2022-08-01T14:48:51.084010Z",
+ "iopub.status.busy": "2022-08-01T14:48:51.083431Z",
+ "iopub.status.idle": "2022-08-01T14:48:51.116081Z",
+ "shell.execute_reply": "2022-08-01T14:48:51.115133Z",
+ "shell.execute_reply.started": "2022-08-01T14:48:51.083974Z"
},
"tags": []
},
@@ -353,7 +352,7 @@
"
1.385714 | \n",
" 0.030043 | \n",
" 23.333333 | \n",
- " 3136.333333 | \n",
+ " 5.760612 | \n",
" \n",
" \n",
" 111 | \n",
@@ -369,7 +368,7 @@
" 1.285714 | \n",
" 0.032957 | \n",
" 23.333333 | \n",
- " 2700.000000 | \n",
+ " 4.959184 | \n",
"
\n",
" \n",
" 243 | \n",
@@ -385,7 +384,7 @@
" 1.375000 | \n",
" 0.029412 | \n",
" 26.666667 | \n",
- " 4033.333333 | \n",
+ " 5.671875 | \n",
"
\n",
" \n",
" 334 | \n",
@@ -401,7 +400,7 @@
" 1.428571 | \n",
" 0.028926 | \n",
" 23.333333 | \n",
- " 3333.333333 | \n",
+ " 6.122449 | \n",
"
\n",
" \n",
"\n",
@@ -420,11 +419,11 @@
"243 77 3 mazda rx-4 1.375000 0.029412 26.666667 \n",
"334 80 3 mazda rx-7 gs 1.428571 0.028926 23.333333 \n",
"\n",
- " grunt \n",
- "71 3136.333333 \n",
- "111 2700.000000 \n",
- "243 4033.333333 \n",
- "334 3333.333333 "
+ " grunt \n",
+ "71 5.760612 \n",
+ "111 4.959184 \n",
+ "243 5.671875 \n",
+ "334 6.122449 "
]
},
"execution_count": 6,
@@ -453,11 +452,11 @@
"id": "5eda8f40-bff6-4715-ba54-b083c74b039d",
"metadata": {
"execution": {
- "iopub.execute_input": "2022-08-01T04:20:12.371148Z",
- "iopub.status.busy": "2022-08-01T04:20:12.370520Z",
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- "shell.execute_reply": "2022-08-01T04:20:12.488016Z",
- "shell.execute_reply.started": "2022-08-01T04:20:12.371118Z"
+ "iopub.execute_input": "2022-08-01T14:48:51.121197Z",
+ "iopub.status.busy": "2022-08-01T14:48:51.120558Z",
+ "iopub.status.idle": "2022-08-01T14:48:51.303457Z",
+ "shell.execute_reply": "2022-08-01T14:48:51.302625Z",
+ "shell.execute_reply.started": "2022-08-01T14:48:51.121166Z"
},
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@@ -488,11 +487,11 @@
"id": "1476617f-8097-4294-8c42-fb86ff96c1d0",
"metadata": {
"execution": {
- "iopub.execute_input": "2022-08-01T04:20:12.489303Z",
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- "shell.execute_reply": "2022-08-01T04:20:12.574107Z",
- "shell.execute_reply.started": "2022-08-01T04:20:12.489288Z"
+ "iopub.execute_input": "2022-08-01T14:48:51.304784Z",
+ "iopub.status.busy": "2022-08-01T14:48:51.304504Z",
+ "iopub.status.idle": "2022-08-01T14:48:51.460139Z",
+ "shell.execute_reply": "2022-08-01T14:48:51.459313Z",
+ "shell.execute_reply.started": "2022-08-01T14:48:51.304758Z"
},
"tags": []
},
@@ -531,11 +530,11 @@
"id": "c7aece22-1e78-4a48-b969-f1207ba09aad",
"metadata": {
"execution": {
- "iopub.execute_input": "2022-08-01T04:20:12.575478Z",
- "iopub.status.busy": "2022-08-01T04:20:12.575129Z",
- "iopub.status.idle": "2022-08-01T04:20:12.588438Z",
- "shell.execute_reply": "2022-08-01T04:20:12.587822Z",
- "shell.execute_reply.started": "2022-08-01T04:20:12.575463Z"
+ "iopub.execute_input": "2022-08-01T14:48:51.461824Z",
+ "iopub.status.busy": "2022-08-01T14:48:51.461525Z",
+ "iopub.status.idle": "2022-08-01T14:48:51.483317Z",
+ "shell.execute_reply": "2022-08-01T14:48:51.482548Z",
+ "shell.execute_reply.started": "2022-08-01T14:48:51.461798Z"
},
"tags": []
},
@@ -591,7 +590,7 @@
" 0.533333 | \n",
" 0.045340 | \n",
" 22.500000 | \n",
- " 576.000000 | \n",
+ " 1.137778 | \n",
" \n",
" \n",
" 325 | \n",
@@ -607,7 +606,7 @@
" 0.533333 | \n",
" 0.043165 | \n",
" 22.500000 | \n",
- " 576.000000 | \n",
+ " 1.137778 | \n",
"
\n",
" \n",
" 326 | \n",
@@ -623,7 +622,7 @@
" 0.533333 | \n",
" 0.038544 | \n",
" 22.500000 | \n",
- " 576.000000 | \n",
+ " 1.137778 | \n",
"
\n",
" \n",
" 327 | \n",
@@ -639,7 +638,7 @@
" 0.553719 | \n",
" 0.041017 | \n",
" 24.200000 | \n",
- " 897.800000 | \n",
+ " 1.533024 | \n",
"
\n",
" \n",
" 358 | \n",
@@ -655,7 +654,7 @@
" 0.567376 | \n",
" 0.043653 | \n",
" 35.250000 | \n",
- " 1600.000000 | \n",
+ " 1.287662 | \n",
"
\n",
" \n",
" 359 | \n",
@@ -671,7 +670,7 @@
" 0.524138 | \n",
" 0.045886 | \n",
" 24.166667 | \n",
- " 962.666667 | \n",
+ " 1.648323 | \n",
"
\n",
" \n",
" 386 | \n",
@@ -687,7 +686,7 @@
" 0.324427 | \n",
" 0.086899 | \n",
" 43.666667 | \n",
- " 1204.166667 | \n",
+ " 0.631519 | \n",
"
\n",
" \n",
"\n",
@@ -712,14 +711,14 @@
"359 81 2 volvo diesel 0.524138 \n",
"386 82 1 oldsmobile cutlass ciera (diesel) 0.324427 \n",
"\n",
- " load bore_size grunt \n",
- "244 0.045340 22.500000 576.000000 \n",
- "325 0.043165 22.500000 576.000000 \n",
- "326 0.038544 22.500000 576.000000 \n",
- "327 0.041017 24.200000 897.800000 \n",
- "358 0.043653 35.250000 1600.000000 \n",
- "359 0.045886 24.166667 962.666667 \n",
- "386 0.086899 43.666667 1204.166667 "
+ " load bore_size grunt \n",
+ "244 0.045340 22.500000 1.137778 \n",
+ "325 0.043165 22.500000 1.137778 \n",
+ "326 0.038544 22.500000 1.137778 \n",
+ "327 0.041017 24.200000 1.533024 \n",
+ "358 0.043653 35.250000 1.287662 \n",
+ "359 0.045886 24.166667 1.648323 \n",
+ "386 0.086899 43.666667 0.631519 "
]
},
"execution_count": 9,
@@ -746,11 +745,11 @@
"id": "92f0bf1a-af7b-4a26-b422-8ca01fdfde1b",
"metadata": {
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- "iopub.execute_input": "2022-08-01T04:20:12.590154Z",
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- "shell.execute_reply": "2022-08-01T04:20:12.713877Z",
- "shell.execute_reply.started": "2022-08-01T04:20:12.590124Z"
+ "iopub.execute_input": "2022-08-01T14:48:51.484935Z",
+ "iopub.status.busy": "2022-08-01T14:48:51.484399Z",
+ "iopub.status.idle": "2022-08-01T14:48:51.694203Z",
+ "shell.execute_reply": "2022-08-01T14:48:51.693458Z",
+ "shell.execute_reply.started": "2022-08-01T14:48:51.484907Z"
},
"tags": []
},
@@ -789,11 +788,11 @@
"id": "0fb1ed64-bba6-463c-9a0f-84af360515b5",
"metadata": {
"execution": {
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},
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},
@@ -849,7 +848,7 @@
" 0.324427 | \n",
" 0.086899 | \n",
" 43.666667 | \n",
- " 1204.166667 | \n",
+ " 0.631519 | \n",
" \n",
" \n",
"\n",
@@ -862,8 +861,8 @@
" model_year origin car_name efficiency \\\n",
"386 82 1 oldsmobile cutlass ciera (diesel) 0.324427 \n",
"\n",
- " load bore_size grunt \n",
- "386 0.086899 43.666667 1204.166667 "
+ " load bore_size grunt \n",
+ "386 0.086899 43.666667 0.631519 "
]
},
"execution_count": 11,
@@ -905,11 +904,11 @@
"id": "c0c4f183-ef44-42ee-b64c-a75c63450d7b",
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- "shell.execute_reply.started": "2022-08-01T04:20:12.727919Z"
+ "iopub.execute_input": "2022-08-01T14:48:51.713333Z",
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+ "shell.execute_reply.started": "2022-08-01T14:48:51.713306Z"
},
"tags": []
},
@@ -965,7 +964,7 @@
" 0.357143 | \n",
" 0.089744 | \n",
" 43.75 | \n",
- " 1953.125 | \n",
+ " 1.020408 | \n",
" \n",
" \n",
" 363 | \n",
@@ -981,7 +980,7 @@
" 0.300000 | \n",
" 0.093960 | \n",
" 43.75 | \n",
- " 1378.125 | \n",
+ " 0.720000 | \n",
"
\n",
" \n",
"\n",
@@ -997,8 +996,8 @@
"363 81 1 oldsmobile cutlass ls 0.300000 0.093960 \n",
"\n",
" bore_size grunt \n",
- "298 43.75 1953.125 \n",
- "363 43.75 1378.125 "
+ "298 43.75 1.020408 \n",
+ "363 43.75 0.720000 "
]
},
"execution_count": 12,
@@ -1024,11 +1023,11 @@
"id": "8f51f87e-fb76-4c8a-b4bc-05f147fc8efa",
"metadata": {
"execution": {
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- "shell.execute_reply.started": "2022-08-01T04:20:12.756186Z"
+ "iopub.execute_input": "2022-08-01T14:48:51.735142Z",
+ "iopub.status.busy": "2022-08-01T14:48:51.734785Z",
+ "iopub.status.idle": "2022-08-01T14:48:51.750660Z",
+ "shell.execute_reply": "2022-08-01T14:48:51.749934Z",
+ "shell.execute_reply.started": "2022-08-01T14:48:51.735114Z"
},
"tags": []
},
@@ -1084,7 +1083,7 @@
" 0.494505 | \n",
" 0.14744 | \n",
" 56.875 | \n",
- " 6328.125 | \n",
+ " 1.956285 | \n",
" \n",
" \n",
"\n",
@@ -1098,7 +1097,7 @@
"13 70 1 buick estate wagon (sw) 0.494505 0.14744 \n",
"\n",
" bore_size grunt \n",
- "13 56.875 6328.125 "
+ "13 56.875 1.956285 "
]
},
"execution_count": 13,
@@ -1124,11 +1123,11 @@
"id": "7d556866-da6d-48dd-b37a-e59c3155085d",
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- "shell.execute_reply.started": "2022-08-01T04:20:12.772385Z"
+ "iopub.execute_input": "2022-08-01T14:48:51.752120Z",
+ "iopub.status.busy": "2022-08-01T14:48:51.751768Z",
+ "iopub.status.idle": "2022-08-01T14:48:51.757117Z",
+ "shell.execute_reply": "2022-08-01T14:48:51.756287Z",
+ "shell.execute_reply.started": "2022-08-01T14:48:51.752093Z"
},
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@@ -1152,11 +1151,11 @@
"id": "558d450a-2649-4005-bbe8-5f8cc509f965",
"metadata": {
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- "shell.execute_reply": "2022-08-01T04:20:12.929878Z",
- "shell.execute_reply.started": "2022-08-01T04:20:12.778459Z"
+ "iopub.execute_input": "2022-08-01T14:48:51.758801Z",
+ "iopub.status.busy": "2022-08-01T14:48:51.758192Z",
+ "iopub.status.idle": "2022-08-01T14:48:52.022488Z",
+ "shell.execute_reply": "2022-08-01T14:48:52.021738Z",
+ "shell.execute_reply.started": "2022-08-01T14:48:51.758773Z"
},
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@@ -1203,11 +1202,11 @@
"id": "38935e91-3877-47a3-96d6-cd54e2704bdb",
"metadata": {
"execution": {
- "iopub.execute_input": "2022-08-01T04:20:12.931405Z",
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- "shell.execute_reply.started": "2022-08-01T04:20:12.931389Z"
+ "iopub.execute_input": "2022-08-01T14:48:52.023871Z",
+ "iopub.status.busy": "2022-08-01T14:48:52.023532Z",
+ "iopub.status.idle": "2022-08-01T14:48:52.046271Z",
+ "shell.execute_reply": "2022-08-01T14:48:52.045474Z",
+ "shell.execute_reply.started": "2022-08-01T14:48:52.023845Z"
},
"tags": []
},
@@ -1263,7 +1262,7 @@
" 0.755814 | \n",
" 0.040758 | \n",
" 21.50 | \n",
- " 1056.2500 | \n",
+ " 2.285019 | \n",
" \n",
" \n",
" 329 | \n",
@@ -1279,7 +1278,7 @@
" 0.736264 | \n",
" 0.049189 | \n",
" 22.75 | \n",
- " 1122.2500 | \n",
+ " 2.168337 | \n",
"
\n",
" \n",
" 325 | \n",
@@ -1295,7 +1294,7 @@
" 0.533333 | \n",
" 0.043165 | \n",
" 22.50 | \n",
- " 576.0000 | \n",
+ " 1.137778 | \n",
"
\n",
" \n",
" 393 | \n",
@@ -1311,7 +1310,7 @@
" 0.536082 | \n",
" 0.045540 | \n",
" 24.25 | \n",
- " 676.0000 | \n",
+ " 1.149538 | \n",
"
\n",
" \n",
" 326 | \n",
@@ -1327,7 +1326,7 @@
" 0.533333 | \n",
" 0.038544 | \n",
" 22.50 | \n",
- " 576.0000 | \n",
+ " 1.137778 | \n",
"
\n",
" \n",
" 244 | \n",
@@ -1343,7 +1342,7 @@
" 0.533333 | \n",
" 0.045340 | \n",
" 22.50 | \n",
- " 576.0000 | \n",
+ " 1.137778 | \n",
"
\n",
" \n",
" 309 | \n",
@@ -1359,7 +1358,7 @@
" 0.775510 | \n",
" 0.045709 | \n",
" 24.50 | \n",
- " 1444.0000 | \n",
+ " 2.405664 | \n",
"
\n",
" \n",
" 330 | \n",
@@ -1375,7 +1374,7 @@
" 0.629412 | \n",
" 0.046322 | \n",
" 21.25 | \n",
- " 715.5625 | \n",
+ " 1.584637 | \n",
"
\n",
" \n",
" 324 | \n",
@@ -1391,7 +1390,7 @@
" 0.764706 | \n",
" 0.040284 | \n",
" 21.25 | \n",
- " 1056.2500 | \n",
+ " 2.339100 | \n",
"
\n",
" \n",
" 247 | \n",
@@ -1407,7 +1406,7 @@
" 0.823529 | \n",
" 0.041063 | \n",
" 21.25 | \n",
- " 1225.0000 | \n",
+ " 2.712803 | \n",
"
\n",
" \n",
"\n",
@@ -1438,17 +1437,17 @@
"324 80 3 datsun 210 0.764706 \n",
"247 78 3 datsun b210 gx 0.823529 \n",
"\n",
- " load bore_size grunt \n",
- "322 0.040758 21.50 1056.2500 \n",
- "329 0.049189 22.75 1122.2500 \n",
- "325 0.043165 22.50 576.0000 \n",
- "393 0.045540 24.25 676.0000 \n",
- "326 0.038544 22.50 576.0000 \n",
- "244 0.045340 22.50 576.0000 \n",
- "309 0.045709 24.50 1444.0000 \n",
- "330 0.046322 21.25 715.5625 \n",
- "324 0.040284 21.25 1056.2500 \n",
- "247 0.041063 21.25 1225.0000 "
+ " load bore_size grunt \n",
+ "322 0.040758 21.50 2.285019 \n",
+ "329 0.049189 22.75 2.168337 \n",
+ "325 0.043165 22.50 1.137778 \n",
+ "393 0.045540 24.25 1.149538 \n",
+ "326 0.038544 22.50 1.137778 \n",
+ "244 0.045340 22.50 1.137778 \n",
+ "309 0.045709 24.50 2.405664 \n",
+ "330 0.046322 21.25 1.584637 \n",
+ "324 0.040284 21.25 2.339100 \n",
+ "247 0.041063 21.25 2.712803 "
]
},
"execution_count": 16,
@@ -1474,11 +1473,11 @@
"id": "65588fe3-762f-42b0-9427-feb64275b792",
"metadata": {
"execution": {
- "iopub.execute_input": "2022-08-01T04:20:12.948105Z",
- "iopub.status.busy": "2022-08-01T04:20:12.947948Z",
- "iopub.status.idle": "2022-08-01T04:20:13.102377Z",
- "shell.execute_reply": "2022-08-01T04:20:13.101717Z",
- "shell.execute_reply.started": "2022-08-01T04:20:12.948090Z"
+ "iopub.execute_input": "2022-08-01T14:48:52.047810Z",
+ "iopub.status.busy": "2022-08-01T14:48:52.047441Z",
+ "iopub.status.idle": "2022-08-01T14:48:52.290693Z",
+ "shell.execute_reply": "2022-08-01T14:48:52.289858Z",
+ "shell.execute_reply.started": "2022-08-01T14:48:52.047782Z"
},
"tags": []
},
@@ -1525,11 +1524,11 @@
"id": "1497a48c-42a3-447e-b1fb-e3a5b78902da",
"metadata": {
"execution": {
- "iopub.execute_input": "2022-08-01T04:20:13.103850Z",
- "iopub.status.busy": "2022-08-01T04:20:13.103446Z",
- "iopub.status.idle": "2022-08-01T04:20:13.131408Z",
- "shell.execute_reply": "2022-08-01T04:20:13.130488Z",
- "shell.execute_reply.started": "2022-08-01T04:20:13.103820Z"
+ "iopub.execute_input": "2022-08-01T14:48:52.292148Z",
+ "iopub.status.busy": "2022-08-01T14:48:52.291798Z",
+ "iopub.status.idle": "2022-08-01T14:48:52.315086Z",
+ "shell.execute_reply": "2022-08-01T14:48:52.314262Z",
+ "shell.execute_reply.started": "2022-08-01T14:48:52.292121Z"
},
"tags": []
},
@@ -1585,7 +1584,7 @@
" 0.634868 | \n",
" 0.064243 | \n",
" 38.000 | \n",
- " 4656.125 | \n",
+ " 3.224463 | \n",
" \n",
" \n",
" 26 | \n",
@@ -1601,7 +1600,7 @@
" 0.651466 | \n",
" 0.070155 | \n",
" 38.375 | \n",
- " 5000.000 | \n",
+ " 3.395261 | \n",
"
\n",
" \n",
" 25 | \n",
@@ -1617,7 +1616,7 @@
" 0.597222 | \n",
" 0.078007 | \n",
" 45.000 | \n",
- " 5778.125 | \n",
+ " 2.853395 | \n",
"
\n",
" \n",
" 27 | \n",
@@ -1633,7 +1632,7 @@
" 0.660377 | \n",
" 0.072570 | \n",
" 39.750 | \n",
- " 5512.500 | \n",
+ " 3.488786 | \n",
"
\n",
" \n",
" 103 | \n",
@@ -1649,7 +1648,7 @@
" 0.375000 | \n",
" 0.080048 | \n",
" 50.000 | \n",
- " 2812.500 | \n",
+ " 1.125000 | \n",
"
\n",
" \n",
" 67 | \n",
@@ -1665,7 +1664,7 @@
" 0.484848 | \n",
" 0.092597 | \n",
" 53.625 | \n",
- " 5408.000 | \n",
+ " 1.880624 | \n",
"
\n",
" \n",
" 124 | \n",
@@ -1681,7 +1680,7 @@
" 0.514286 | \n",
" 0.095524 | \n",
" 43.750 | \n",
- " 4050.000 | \n",
+ " 2.115918 | \n",
"
\n",
" \n",
" 42 | \n",
@@ -1697,7 +1696,7 @@
" 0.469974 | \n",
" 0.077296 | \n",
" 47.875 | \n",
- " 4050.000 | \n",
+ " 1.767004 | \n",
"
\n",
" \n",
" 95 | \n",
@@ -1713,7 +1712,7 @@
" 0.494505 | \n",
" 0.091901 | \n",
" 56.875 | \n",
- " 6328.125 | \n",
+ " 1.956285 | \n",
"
\n",
" \n",
" 90 | \n",
@@ -1729,7 +1728,7 @@
" 0.461538 | \n",
" 0.086632 | \n",
" 53.625 | \n",
- " 4900.500 | \n",
+ " 1.704142 | \n",
"
\n",
" \n",
"\n",
@@ -1761,16 +1760,16 @@
"90 73 1 mercury marquis brougham 0.461538 0.086632 \n",
"\n",
" bore_size grunt \n",
- "28 38.000 4656.125 \n",
- "26 38.375 5000.000 \n",
- "25 45.000 5778.125 \n",
- "27 39.750 5512.500 \n",
- "103 50.000 2812.500 \n",
- "67 53.625 5408.000 \n",
- "124 43.750 4050.000 \n",
- "42 47.875 4050.000 \n",
- "95 56.875 6328.125 \n",
- "90 53.625 4900.500 "
+ "28 38.000 3.224463 \n",
+ "26 38.375 3.395261 \n",
+ "25 45.000 2.853395 \n",
+ "27 39.750 3.488786 \n",
+ "103 50.000 1.125000 \n",
+ "67 53.625 1.880624 \n",
+ "124 43.750 2.115918 \n",
+ "42 47.875 1.767004 \n",
+ "95 56.875 1.956285 \n",
+ "90 53.625 1.704142 "
]
},
"execution_count": 18,
@@ -1796,11 +1795,11 @@
"id": "8710cba8-6b7e-4219-98b9-b7d5a1b4f4b9",
"metadata": {
"execution": {
- "iopub.execute_input": "2022-08-01T04:20:13.132876Z",
- "iopub.status.busy": "2022-08-01T04:20:13.132574Z",
- "iopub.status.idle": "2022-08-01T04:20:13.142096Z",
- "shell.execute_reply": "2022-08-01T04:20:13.141321Z",
- "shell.execute_reply.started": "2022-08-01T04:20:13.132851Z"
+ "iopub.execute_input": "2022-08-01T14:48:52.316598Z",
+ "iopub.status.busy": "2022-08-01T14:48:52.316192Z",
+ "iopub.status.idle": "2022-08-01T14:48:52.324768Z",
+ "shell.execute_reply": "2022-08-01T14:48:52.324017Z",
+ "shell.execute_reply.started": "2022-08-01T14:48:52.316570Z"
},
"tags": []
},
@@ -1815,7 +1814,7 @@
"efficiency mean: 0.61\n",
"load mean: 0.06\n",
"bore_size mean: 33.36\n",
- "grunt mean: 2060.50\n"
+ "grunt mean: 1.92\n"
]
}
],
@@ -1842,11 +1841,11 @@
"id": "7205bdab-a7df-41b4-9ec0-c1c9e2fe1c03",
"metadata": {
"execution": {
- "iopub.execute_input": "2022-08-01T04:20:13.143792Z",
- "iopub.status.busy": "2022-08-01T04:20:13.143335Z",
- "iopub.status.idle": "2022-08-01T04:20:13.153208Z",
- "shell.execute_reply": "2022-08-01T04:20:13.152547Z",
- "shell.execute_reply.started": "2022-08-01T04:20:13.143758Z"
+ "iopub.execute_input": "2022-08-01T14:48:52.326254Z",
+ "iopub.status.busy": "2022-08-01T14:48:52.325834Z",
+ "iopub.status.idle": "2022-08-01T14:48:52.339352Z",
+ "shell.execute_reply": "2022-08-01T14:48:52.338521Z",
+ "shell.execute_reply.started": "2022-08-01T14:48:52.326227Z"
},
"tags": []
},
@@ -1860,7 +1859,7 @@
"cylinders -0.776090\n",
"bore_size -0.773403\n",
"load -0.724271\n",
- "grunt -0.644081\n",
+ "grunt 0.180568\n",
"acceleration 0.420414\n",
"efficiency 0.509309\n",
"origin 0.563833\n",
@@ -1903,11 +1902,11 @@
"id": "52d0ffbf-55aa-49b9-b99f-8160bf09cc79",
"metadata": {
"execution": {
- "iopub.execute_input": "2022-08-01T04:20:13.154483Z",
- "iopub.status.busy": "2022-08-01T04:20:13.154106Z",
- "iopub.status.idle": "2022-08-01T04:20:13.159628Z",
- "shell.execute_reply": "2022-08-01T04:20:13.158886Z",
- "shell.execute_reply.started": "2022-08-01T04:20:13.154458Z"
+ "iopub.execute_input": "2022-08-01T14:48:52.340843Z",
+ "iopub.status.busy": "2022-08-01T14:48:52.340494Z",
+ "iopub.status.idle": "2022-08-01T14:48:52.347303Z",
+ "shell.execute_reply": "2022-08-01T14:48:52.346318Z",
+ "shell.execute_reply.started": "2022-08-01T14:48:52.340816Z"
},
"tags": []
},
@@ -1936,11 +1935,11 @@
"id": "6a4a9e48-57a1-48b6-b289-58bc43584112",
"metadata": {
"execution": {
- "iopub.execute_input": "2022-08-01T04:20:13.163437Z",
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- "iopub.status.idle": "2022-08-01T04:20:13.175359Z",
- "shell.execute_reply": "2022-08-01T04:20:13.174579Z",
- "shell.execute_reply.started": "2022-08-01T04:20:13.163422Z"
+ "iopub.execute_input": "2022-08-01T14:48:52.352022Z",
+ "iopub.status.busy": "2022-08-01T14:48:52.351247Z",
+ "iopub.status.idle": "2022-08-01T14:48:52.367555Z",
+ "shell.execute_reply": "2022-08-01T14:48:52.366775Z",
+ "shell.execute_reply.started": "2022-08-01T14:48:52.351982Z"
},
"tags": []
},
diff --git a/img/bore_size_joint.png b/img/bore_size_joint.png
index 82b7924..5d5ab8e 100644
Binary files a/img/bore_size_joint.png and b/img/bore_size_joint.png differ
diff --git a/img/ci_per_cyl_joint.png b/img/ci_per_cyl_joint.png
deleted file mode 100644
index a605f1a..0000000
Binary files a/img/ci_per_cyl_joint.png and /dev/null differ
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deleted file mode 100644
index f6e2b58..0000000
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diff --git a/img/cylinders_joint.png b/img/cylinders_joint.png
index fee7f3d..f65c6d2 100644
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diff --git a/img/displacement_joint.png b/img/displacement_joint.png
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diff --git a/img/efficiency_joint.png b/img/efficiency_joint.png
index ea637ba..4185558 100644
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diff --git a/img/grunt_joint.png b/img/grunt_joint.png
index 2678ba6..27f00bc 100644
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diff --git a/img/gruntiness_joint.png b/img/gruntiness_joint.png
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diff --git a/img/horsepower_joint.png b/img/horsepower_joint.png
index 46dd6af..a65f0d5 100644
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diff --git a/img/hp_per_ci_joint.png b/img/hp_per_ci_joint.png
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diff --git a/img/load_joint.png b/img/load_joint.png
index 6bd79fb..864250d 100644
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diff --git a/img/weight_joint.png b/img/weight_joint.png
index 102b9ef..8e85099 100644
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diff --git a/model.ipynb b/model.ipynb
index 2c4f823..bfb2fe7 100644
--- a/model.ipynb
+++ b/model.ipynb
@@ -8,17 +8,25 @@
"[EDA](eda.ipynb)"
]
},
+ {
+ "cell_type": "markdown",
+ "id": "43c4fe12-eb94-434c-8808-15fd7cdcf17d",
+ "metadata": {},
+ "source": [
+ "# Modeling"
+ ]
+ },
{
"cell_type": "code",
"execution_count": 1,
"id": "c47122c5-bdcd-4b6b-8d22-8958ad910eca",
"metadata": {
"execution": {
- "iopub.execute_input": "2022-07-21T20:30:04.392164Z",
- "iopub.status.busy": "2022-07-21T20:30:04.391759Z",
- "iopub.status.idle": "2022-07-21T20:30:06.057099Z",
- "shell.execute_reply": "2022-07-21T20:30:06.056318Z",
- "shell.execute_reply.started": "2022-07-21T20:30:04.392085Z"
+ "iopub.execute_input": "2022-08-01T14:49:27.108272Z",
+ "iopub.status.busy": "2022-08-01T14:49:27.107585Z",
+ "iopub.status.idle": "2022-08-01T14:49:28.795162Z",
+ "shell.execute_reply": "2022-08-01T14:49:28.794368Z",
+ "shell.execute_reply.started": "2022-08-01T14:49:27.108146Z"
},
"tags": []
},
@@ -29,52 +37,1131 @@
"import matplotlib.pyplot as plt\n",
"from sklearn.model_selection import train_test_split\n",
"from sklearn.pipeline import Pipeline\n",
- "from sklearn.preprocessing import (StandardScaler,\n",
- " QuantileTransformer,\n",
- " Normalizer,\n",
- " MinMaxScaler,\n",
- " RobustScaler,\n",
- " PowerTransformer)\n",
- "\n",
- "from sklearn.linear_model import (Lars,\n",
- " Ridge,\n",
- " Lasso,\n",
- " LarsCV,\n",
- " LassoCV,\n",
- " RidgeCV,\n",
- " LassoLars,\n",
- " ElasticNet,\n",
- " LassoLarsCV,\n",
- " LassoLarsIC,\n",
- " ElasticNetCV,\n",
- " SGDRegressor,\n",
- " LinearRegression,\n",
- " OrthogonalMatchingPursuit,\n",
- " OrthogonalMatchingPursuitCV)\n",
- "\n",
+ "from sklearn.preprocessing import QuantileTransformer\n",
+ "from sklearn.linear_model import Ridge,Lasso,LinearRegression\n",
+ "from sklearn.tree import DecisionTreeRegressor\n",
"from sklearn.neighbors import KNeighborsRegressor\n",
"from sklearn.svm import LinearSVR\n",
- "from sklearn.metrics import mean_squared_error, r2_score"
+ "from sklearn.metrics import mean_squared_error,r2_score"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "1cbc710d-f819-4200-9add-25bc699d8b46",
+ "metadata": {},
+ "source": [
+ "Load in the data"
]
},
{
"cell_type": "code",
"execution_count": 2,
- "id": "8c3b98e1-9a8f-4d42-8a29-5d030934a4ed",
+ "id": "78f30ccd-7153-4d8e-9784-4dce46a46fb2",
"metadata": {
"execution": {
- "iopub.execute_input": "2022-07-21T20:30:06.059480Z",
- "iopub.status.busy": "2022-07-21T20:30:06.059058Z",
- "iopub.status.idle": "2022-07-21T20:30:11.086526Z",
- "shell.execute_reply": "2022-07-21T20:30:11.085657Z",
- "shell.execute_reply.started": "2022-07-21T20:30:06.059453Z"
+ "iopub.execute_input": "2022-08-01T14:49:28.797832Z",
+ "iopub.status.busy": "2022-08-01T14:49:28.797191Z",
+ "iopub.status.idle": "2022-08-01T14:49:28.858368Z",
+ "shell.execute_reply": "2022-08-01T14:49:28.857624Z",
+ "shell.execute_reply.started": "2022-08-01T14:49:28.797801Z"
+ },
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "X_e = pd.read_csv('data/X_engineered.csv')\n",
+ "X_s = pd.read_csv('data/X_straight.csv')\n",
+ "y = pd.read_csv('data/y.csv').mpg"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "046eba55-3375-4e28-8776-1bec54e4f72f",
+ "metadata": {},
+ "source": [
+ "Transform it, QuantileTransformer works best in my testing"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "cd8eb496-d624-49a5-b1c8-0e1bed4abc1e",
+ "metadata": {
+ "execution": {
+ "iopub.execute_input": "2022-08-01T14:49:28.860006Z",
+ "iopub.status.busy": "2022-08-01T14:49:28.859406Z",
+ "iopub.status.idle": "2022-08-01T14:49:28.876483Z",
+ "shell.execute_reply": "2022-08-01T14:49:28.875734Z",
+ "shell.execute_reply.started": "2022-08-01T14:49:28.859962Z"
+ },
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "qt = QuantileTransformer(n_quantiles=297)\n",
+ "qt_eng = qt.fit_transform(X_e)\n",
+ "qt_str = qt.fit_transform(X_s)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "9fa8177f-8491-4a10-8515-4678c25a1abe",
+ "metadata": {
+ "execution": {
+ "iopub.execute_input": "2022-08-01T14:49:28.878114Z",
+ "iopub.status.busy": "2022-08-01T14:49:28.877540Z",
+ "iopub.status.idle": "2022-08-01T14:49:28.888152Z",
+ "shell.execute_reply": "2022-08-01T14:49:28.887394Z",
+ "shell.execute_reply.started": "2022-08-01T14:49:28.878087Z"
+ },
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "def run(X,y,model_type):\n",
+ " r2_test_list = []\n",
+ " r2_train_list = []\n",
+ " rmse_test_list = []\n",
+ " rmse_train_list = []\n",
+ " \n",
+ " for i in range(201):\n",
+ " X_train, X_test, y_train, y_test = train_test_split(X, y)\n",
+ " \n",
+ " model = model_type.fit(X_train,y_train)\n",
+ " test_predict = model.predict(X_test)\n",
+ " train_predict = model.predict(X_train)\n",
+ " \n",
+ " r2_test = r2_score(y_test, test_predict)\n",
+ " r2_train = r2_score(y_train, train_predict)\n",
+ " rmse_test = mean_squared_error(y_test, test_predict ,squared=False)\n",
+ " rmse_train = mean_squared_error(y_train, train_predict ,squared=False)\n",
+ " \n",
+ " r2_test_list.append(r2_test)\n",
+ " r2_train_list.append(r2_train)\n",
+ " rmse_test_list.append(rmse_test)\n",
+ " rmse_train_list.append(rmse_train)\n",
+ "\n",
+ " plt.subplots(figsize=(10,6))\n",
+ " plt.title('R-squared over 200 iterations')\n",
+ " plt.plot(r2_test_list,label='R2 Test')\n",
+ " plt.plot(r2_train_list,label='R2 Train')\n",
+ " plt.legend()\n",
+ " plt.show();\n",
+ " \n",
+ " avg = np.mean\n",
+ " print(f'''\\\n",
+ ".-------------------------------------------------.\n",
+ "| R2 Test | R2 Train | RMSE Test | RMSE Train |\n",
+ "|-----------|----------|-------------|------------|\n",
+ "| Min: {min(r2_test_list):.2f} | Min:{min(r2_train_list):.2f} | Min: {min(rmse_test_list):.2f} | Min:{min(rmse_train_list):.2f} |\n",
+ "| Avg: {avg(r2_test_list):.2f} | Avg:{avg(r2_train_list):.2f} | Avg: {avg(rmse_test_list):.2f} | Avg:{avg(rmse_train_list):.2f} |\n",
+ "| Max: {max(r2_test_list):.2f} | Max:{max(r2_train_list):.2f} | Max: {max(rmse_test_list):.2f} | Max:{max(rmse_train_list):.2f} |\n",
+ "'-------------------------------------------------'\n",
+ " ''')\n",
+ " \n",
+ " plt.subplots(figsize=(10,5))\n",
+ " plt.title('RMSE over 200 iterations')\n",
+ " plt.plot(rmse_test_list,label='RMSE Test')\n",
+ " plt.plot(rmse_train_list,label='RMSE Train')\n",
+ " plt.legend()\n",
+ " plt.show();"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "a91815c9-27db-495e-bc3d-1d8d160129de",
+ "metadata": {},
+ "source": [
+ "# Linear Regression"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "9a4029e4-1e8c-442f-ac56-66a8f6aaa62d",
+ "metadata": {
+ "execution": {
+ "iopub.execute_input": "2022-08-01T14:49:28.889515Z",
+ "iopub.status.busy": "2022-08-01T14:49:28.889180Z",
+ "iopub.status.idle": "2022-08-01T14:49:29.884061Z",
+ "shell.execute_reply": "2022-08-01T14:49:29.883304Z",
+ "shell.execute_reply.started": "2022-08-01T14:49:28.889488Z"
+ },
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Linear Regression With Engineered Features\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "