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feature-selection

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

Jupyter Notebook
1540
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
1078
8 个月前

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
702
10 个月前

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

Python
677
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
642
2 个月前

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

Python
583
5 个月前

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

Jupyter Notebook
577
10 个月前

Linear Prediction Model with Automated Feature Engineering and Selection Capabilities

Python
513
1 个月前

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

Python
509
4 个月前

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

Python
416
2 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++
401
6 天前