Description: Python implementation of principal component regression algorithm for prediction
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File list (Check if you may need any files):
| Filename | Size | Date |
|---|
| PCAR | 0 | 2020-03-27
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| PCAR\.idea | 0 | 2020-03-27
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| PCAR\.idea\misc.xml | 294 | 2020-03-27
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| PCAR\.idea\modules.xml | 267 | 2020-03-27
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| PCAR\.idea\PCAR.iml | 464 | 2020-03-27
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| PCAR\.idea\workspace.xml | 13491 | 2020-03-27
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| PCAR\.ipynb_checkpoints | 0 | 2020-03-27
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| PCAR\.ipynb_checkpoints\main-checkpoint.ipynb | 3421 | 2020-03-27
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| PCAR\main.ipynb | 3421 | 2020-03-27
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| PCAR\main.py | 587 | 2020-03-27
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| PCAR\source | 0 | 2020-03-27
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| PCAR\source\scale.py | 198 | 2020-03-27
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| PCAR\source\sigma_ma.py | 363 | 2020-03-27
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| PCAR\source\sim.py | 297 | 2020-03-27
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| PCAR\source\__pycache__ | 0 | 2020-03-27
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| PCAR\source\__pycache__\pca.cpython-37.pyc | 481 | 2020-03-27
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| PCAR\source\__pycache__\scale.cpython-37.pyc | 403 | 2020-03-27
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| PCAR\source\__pycache__\sigma_ma.cpython-37.pyc | 518 | 2020-03-27
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| PCAR\source\__pycache__\sim.cpython-37.pyc | 524 | 2020-03-27 |
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