36 lines
1.2 KiB
Python
36 lines
1.2 KiB
Python
# ---
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# jupyter:
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# formats: ipynb,py:percent
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# extension: .py
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# format_version: '1.3'
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# jupytext_version: 1.13.0
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# display_name: straw2analysis
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# language: python
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# name: straw2analysis
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# ---
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# %%
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# %matplotlib inline
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import os
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import sys
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import numpy as np
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import matplotlib.pyplot as plt
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import pandas as pd
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# %%
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""" Feature selection pipeline: a methods that can be used in the wrapper metod alongside other wrapper contents (hyperparameter tuning etc.).
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(1) Establish methods for each of the steps in feature selection protocol:
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(a) feature selection inside specific sensors (sklearn method): returns most important features from all sensors
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(b) feature selection between "tuned" sensors: returns filtered sensors, containing most important features retured with (a)
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(2) Ensure that above methods are given only a part of data and use appropriate random seeds - to later simulate use case in production.
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(3) Implement a method which gives graphical exploration of (1) (a) and (b) steps of the feature selection.
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(4) Prepare a core method that can be fit into a wrapper (see sklearn wrapper methods) and integrates methods from (1)
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""" |