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294 search results found

Smile ⭐ 5,833

Statistical Machine Intelligence & Learning Engine

Feature_engine ⭐ 1,651

Feature engineering package with sklearn like functionality

Machine Learning in R

Data Science Complete Tutorial ⭐ 1,575

For extensive instructor led learning

Mlbox ⭐ 1,403

MLBox is a powerful Automated Machine Learning python library.

Boruta_py ⭐ 1,350

Python implementations of the Boruta all-relevant feature selection method.

Data Science Interview Questions And Answers ⭐ 1,169

Data science interview questions with answers. Not ideally (yet)

Sgx Full Orderbook Tick Data Trading Strategy ⭐ 1,151

Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.

Deep_learning_machine_learning_stock ⭐ 1,093

Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.

Nvtabular ⭐ 1,006

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.

Awesome Interpretable Machine Learning ⭐ 856

Feature Engineering And Feature Selection ⭐ 798

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

Lofo Importance ⭐ 785

Leave One Feature Out Importance

EvalML is an AutoML library written in python.

MILK: Machine Learning Toolkit

Featurewiz ⭐ 516

Use advanced feature engineering strategies and select best features from your data set with a single line of code.

Shap Hypetune ⭐ 496

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

Amazing Feature Engineering ⭐ 485

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.

Feature Selection ⭐ 475

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

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

Autofeat ⭐ 410

Linear Prediction Model with Automated Feature Engineering and Selection Capabilities

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

Fast Best-Subset Selection Library

Scikit Rebate ⭐ 308

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

Nlpython ⭐ 302

This repository contains the code related to Natural Language Processing using python scripting language. All the codes are related to my book entitled "Python Natural Language Processing"

Featureselectionga ⭐ 274

Feature Selection using Genetic Algorithm (DEAP Framework)

Data search & enrichment library for Machine Learning → Easily find and add relevant features to your ML & AI pipeline from hundreds of public and premium external data sources, including open & commercial LLMs

My Data Competition Experience ⭐ 271

本人多次机器学习与大数据竞赛Top5的经验总结，满满的干货，拿好不谢

Awesome Domain Adaptation Python Toolbox

Feature Selection For Machine Learning ⭐ 248

Code repository for the online course Feature Selection for Machine Learning

Sklearn Genetic Opt ⭐ 236

ML hyperparameters tuning and features selection, using evolutionary algorithms.

Feature Engineering Tutorials ⭐ 217

Data Science Feature Engineering and Selection Tutorials

zoofs is a python library for performing feature selection using a variety of nature-inspired wrapper algorithms. The algorithms range from swarm-intelligence to physics-based to Evolutionary. It's easy to use , flexible and powerful tool to reduce your feature size.

Flexible Feature Engineering & Exploration Library using GPUs and Optuna.

Machine_learning ⭐ 183

Estudo e implementação dos principais algoritmos de Machine Learning em Jupyter Notebooks.

Parallelized Mutual Information based Feature Selection module.

Wrapper Feature Selection Toolbox Python ⭐ 170

This toolbox offers 13 wrapper feature selection methods (PSO, GA, GWO, HHO, BA, WOA, and etc.) with examples. It is simple and easy to implement.

Powershap ⭐ 153

A power-full Shapley feature selection method.

Compress Fasttext ⭐ 153

Tools for shrinking fastText models (in gensim format)

Boostaroota ⭐ 139

A fast xgboost feature selection algorithm

Python3 binding to mRMR Feature Selection algorithm (currently not maintained)

Dominance Analysis ⭐ 128

This package can be used for dominance analysis or Shapley Value Regression for finding relative importance of predictors on given dataset. This library can be used for key driver analysis or marginal resource allocation models.

Stereo Odometry Soft ⭐ 122

MATLAB Implementation of Visual Odometry using SOFT algorithm

Itmo_fs ⭐ 121

Feature selection library in python

Stability Selection ⭐ 121

scikit-learn compatible implementation of stability selection.

Music Emotion Recognition ⭐ 117

A Machine Learning Approach of Emotional Model

Spark Infotheoretic Feature Selection ⭐ 114

This package contains a generic implementation of greedy Information Theoretic Feature Selection (FS) methods. The implementation is based on the common theoretic framework presented by Gavin Brown. Implementations of mRMR, InfoGain, JMI and other commonly used FS filters are provided.

Pyhsiclasso ⭐ 111

Versatile Nonlinear Feature Selection Algorithm for High-dimensional Data

Relataly Public Python Tutorials ⭐ 109

Beginner-friendly collection of Python notebooks for various use cases of machine learning, deep learning, and analytics. For each notebook there is a separate tutorial on the relataly.com blog.

Pyimpetus ⭐ 106

PyImpetus is a Markov Blanket based feature subset selection algorithm that considers features both separately and together as a group in order to provide not just the best set of features but also the best combination of features

Developer Version of the R package CAST: Caret Applications for Spatio-Temporal models

Microsoft Finance Time Series Forecasting Framework (FinnTS) is a forecasting package that utilizes cutting-edge time series forecasting and parallelization on the cloud to produce accurate forecasts for financial data.

Network Intrusion Detection ⭐ 85

Machine Learning with the NSL-KDD dataset for Network Intrusion Detection

Efficient Algorithms for L0 Regularized Learning

Concrete Autoencoders ⭐ 83

Feature Selection For Machine Learning ⭐ 81

Methods with examples for Feature Selection during Pre-processing in Machine Learning.

All Relevant Feature Selection

HFS: Hierarchical Feature Selection for Efficient Image Segmentation

Fast Mrmr ⭐ 73

An improved implementation of the classical feature selection method: minimum Redundancy and Maximum Relevance (mRMR).

Matlab implementation of TIP2019 paper "Learning Adaptive Discriminative Correlation Filters via Temporal Consistency Preserving Spatial Feature Selection for Robust Visual Object Tracking"

Everything is Linkable

Automated Feature Selection

Geneticalgorithmforfeatureselection ⭐ 60

Search the best feature subset for you classification mode

Ablator is a Service that enables you to roll out functionalities at your own pace, and perform good A/B testing.

Ilearnplus ⭐ 57

iLearnPlus is the first machine-learning platform with both graphical- and web-based user interface that enables the construction of automated machine-learning pipelines for computational analysis and predictions using nucleic acid and protein sequences.

A FEAture Selection Toolbox for C/C+, Java, and Matlab/Octave.

Xuniverse ⭐ 54

xverse (XuniVerse) is collection of transformers for feature engineering and feature selection

Desbordante ⭐ 54

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.

Examples For Data Scientists ⭐ 52

Selective ⭐ 51

Selective: Feature Selection Library

Scrna2019 ⭐ 48

supporting code for the multinomial single cell RNA-Seq paper

Tabnet Modified ⭐ 47

Modification of TabNet as suggested in the Medium article, "The Unreasonable Ineffectiveness of Deep Learning on Tabular Data"

Streamline ⭐ 47

Simple Transparent End-To-End Automated Machine Learning Pipeline for Supervised Learning in Tabular Binary Classification Data

Featureselection ⭐ 47

Feature Selection in R using glmnet-lasso, xgboost and ranger

A Python Package for Feature Selection

Textfeatureselection ⭐ 45

Python library for feature selection for text features. It has filter method, genetic algorithm and TextFeatureSelectionEnsemble for improving text classification models. Helps improve your machine learning models

Python/R library for feature selection in neural nets. ("Feature selection using Stochastic Gates", ICML 2020)

Recipeselectors ⭐ 43

Additional recipes for supervised feature selection to be used with the tidymodels recipes package

Documentfeatureselection ⭐ 37

A set of metrics for feature selection from text data

Efficient feature selection method based on Conditional Mutual Information.

multi-dimensional, multi-sensor, multivariate time series data analysis, unsupervised feature selection, unsupervised deep anomaly detection, and prototype of explainable AI for anomaly detector

Keystone Runtime ⭐ 34

Eyrie enclave runtime kernel

Fselectorrcpp ⭐ 34

Rcpp (free of Java/Weka) implementation of FSelector entropy-based feature selection algorithms with a sparse matrix support

Deep learning for identifying cis-regulatory elements and other applications

Papers_with_code ⭐ 30

paper code with respect to classification, clustering and etc.

Estimation of Distribution algorithms Python package

Mutual Information Feature Selection ⭐ 29

Use mutual information to select features in a Titanic data set

Automatic Feature Selection

Feature Selection for Clustering

Glmpca Py ⭐ 28

generalized principal component analysis (GLM-PCA) implemented in python

Relief Based Algorithms of ReBATE implemented in Python with Cython optimization.

Drugs Recommendation Using Reviews ⭐ 27

Analyzing the Drugs Descriptions, conditions, reviews and then recommending it using Deep Learning Models, for each Health Condition of a Patient.

Py_ml_utils ⭐ 27

Python utilities for Machine Learning competitions

Omicselector ⭐ 26

OmicSelector - Environment, docker-based application and R package for biomarker signiture selection (feature selection) & deep learning diagnostic tool development from high-throughput high-throughput omics experiments and other multidimensional datasets. Initially developed for miRNA-seq, RNA-seq and qPCR.

Fselector ⭐ 26

a Ruby gem for feature selection and ranking

Yandexcatboost Python Demo ⭐ 26

Demo on the capability of Yandex CatBoost gradient boosting classifier on a fictitious IBM HR dataset obtained from Kaggle. Data exploration, cleaning, preprocessing and model tuning are performed on the dataset

Scikit Feature ⭐ 25

2019 Feature Selection ⭐ 24

Research project

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