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feature-selection

A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.

Jupyter Notebook
1595
3 年前

NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.

Python
1095
1 年前

Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.

Jupyter Notebook
741
2 个月前

Features selector based on the self selected-algorithm, loss function and validation method

Python
680
6 年前

Use advanced feature engineering strategies and select best features from your data set with a single line of code. Created by Ram Seshadri. Collaborators welcome.

Python
662
6 个月前

mRMR (minimum-Redundancy-Maximum-Relevance) for automatic feature selection at scale.

Python
602
9 个月前

A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.

Jupyter Notebook
578
1 年前

Linear Prediction Model with Automated Feature Engineering and Selection Capabilities

Python
522
5 个月前

Easy to use Python library of customized functions for cleaning and analyzing data.

Python
520
4 个月前

A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.

Python
419
3 年前

Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.

C++
414
19 天前