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Choosing important features of objects using the rough sets method. Implementation of LEM2 algorithm.

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lem2-important-features

Choosing important features of objects using the rough sets method. Implementation of LEM2 algorithm.

Dataset

Data is collected from "Student alcohol consumption" Kaggle archive

Usage

usage: process.py [--input INPUT] [--column-idx COLUMN_IDX] [--decision-lambda DECISION_LAMBDA] [--bool]

optional arguments: --input INPUT data table input (default: dataset/student-mat.csv) --column-idx COLUMN_IDX decision column index (default: -1) --decision-lambda DECISION_LAMBDA decision lambda(exprert opinion) (default: lambda df: df['G3'] > 10) --bool whether decision column contains bool value, otherwise int (default: False)

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Choosing important features of objects using the rough sets method. Implementation of LEM2 algorithm.

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