Topic: feature-selection Goto Github

👇 Here are 1454 public repositories matching this topic...

abess-team / abess
feature-selection,Fast Best-Subset Selection Library
Organization: abess-team
Home Page: https://abess.readthedocs.io/
polynomial-algorithm high-dimensional-data best-subset-selection machine-learning python r scikit-learn principal-component-analysis linear-regression classification-algorithm

adapt-python / adapt
feature-selection,Awesome Domain Adaptation Python Toolbox
User: adapt-python
Home Page: https://adapt-python.github.io/adapt/
adversarial-learning adversarial-networks dann deep-learning domain-adaptation feature-selection few-shot-learning generalization importance-sampling machine-learning python regularization-parameters scikit-learn tensorflow transfer-learning zero-shot-learning

aerdem4 / lofo-importance
feature-selection,Leave One Feature Out Importance
User: aerdem4
feature-importance machine-learning data-science feature-selection explainable-ai

ajayarunachalam / msda
feature-selection,Library for multi-dimensional, multi-sensor, uni/multivariate time series data analysis, unsupervised feature selection, unsupervised deep anomaly detection, and prototype of explainable AI for anomaly detector
User: ajayarunachalam
signal-processing sensor-data sensor time-series python data-analysis feature-selection feature-engineering variation visualization

akanz1 / klib
feature-selection,Easy to use Python library of customized functions for cleaning and analyzing data.
User: akanz1
Home Page: https://medium.com/p/97191d320f80
data-science data-analysis klib data-visualization python feature-selection data-cleaning data-preprocessing

alteryx / evalml
feature-selection,EvalML is an AutoML library written in python.
Organization: alteryx
Home Page: https://evalml.alteryx.com
automl machine-learning data-science model-selection hyperparameter-tuning optimization feature-engineering feature-selection

anujdutt9 / feature-selection-for-machine-learning
feature-selection,Methods with examples for Feature Selection during Pre-processing in Machine Learning.
User: anujdutt9
feature-selection machine-learning python36 correlation

arnaldog12 / machine_learning
feature-selection,Estudo e implementação dos principais algoritmos de Machine Learning em Jupyter Notebooks.
User: arnaldog12
machine-learning machine-learning-algorithms adaboost decision-trees kmeans knn linear-discriminant-analysis principal-component-analysis naive-bayes regression

ashishpatel26 / amazing-feature-engineering
feature-selection,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.
User: ashishpatel26
feature-engineering machine-learning deep-learning scikit-learn data-mining data-science data-scientists feature-scaling feature-extraction feature-selection

atif-hassan / pyimpetus
feature-selection,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
User: atif-hassan
feature-selection machine-learning-algorithms probability statistics t-test markov-blanket minimal-features

autoviml / featurewiz
feature-selection,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.
User: autoviml
feature-engineering categorical-variables best-encoders feature-engg rfe rfecv feature-extraction feature-selection featuretools xgboost

cerlymarco / shap-hypetune
feature-selection,A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.
User: cerlymarco
parameter-tuning hyperparameter-optimization feature-selection model-selection xgboost lightgbm shap

chasedehan / boostaroota
feature-selection,A fast xgboost feature selection algorithm
User: chasedehan
machine-learning machine-learning-algorithms feature-selection xgboost-algorithm xgboost dimension-reduction algorithm boruta data-science datascientist

cod3licious / autofeat
feature-selection,Linear Prediction Model with Automated Feature Engineering and Selection Capabilities
User: cod3licious
machine-learning machine-learning-models linear-regression feature-engineering feature-selection automl automated-machine-learning automated-feature-engineering automated-data-science

ctlab / itmo_fs
feature-selection,Feature selection library in python
Organization: ctlab
feature-selection machine-learning

cynthiakoopman / network-intrusion-detection
feature-selection,Machine Learning with the NSL-KDD dataset for Network Intrusion Detection
User: cynthiakoopman
nsl-kdd datamining feature-selection network-intrusion-detection intrusion-detection-system machine-learning kdd99 decision-trees random-forest cross-validation

danyalimran93 / music-emotion-recognition
feature-selection,A Machine Learning Approach of Emotional Model
User: danyalimran93
machine-learning data-science feature-extraction feature-selection feature-scaling music-information-retrieval digital-signal-processing librosa

desbordante / desbordante-core
feature-selection,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.
Organization: desbordante
data-analytics data-cleaning data-cleansing data-engineering data-exploration data-mining data-profiling data-science data-wrangling data-preprocessing

dominance-analysis / dominance-analysis
feature-selection,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.
User: dominance-analysis
Home Page: https://pypi.org/project/dominance-analysis/
dominance-analysis relative-importance keydrivers shapley-value regression-models logistic-regression dominance predictor multiple-regression classification-model

duxuhao / feature-selection
feature-selection,Features selector based on the self selected-algorithm, loss function and validation method
User: duxuhao
Home Page: https://pypi.org/project/MLFeatureSelection/
data-science feature-engineering feature-extraction feature-importance feature-selection greedy-search machine-learning

edyoda / data-science-complete-tutorial
feature-selection,For extensive instructor led learning
Organization: edyoda
Home Page: https://www.edyoda.com/program/data-scientist-program
machine-learning scikit-learn linear-regression nearest-neighbors feature-selection decision-trees numpy pandas pipeline

epistasislab / scikit-rebate
feature-selection,A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.
Organization: epistasislab
Home Page: https://EpistasisLab.github.io/scikit-rebate/
feature-selection data-science python

fbrundu / pymrmr
feature-selection,Python3 binding to mRMR Feature Selection algorithm (currently not maintained)
User: fbrundu
feature-selection computational-biology data-science mutual-information gene-expression

feature-engine / feature_engine
feature-selection,Feature engineering package with sklearn like functionality
Organization: feature-engine
Home Page: https://feature-engine.trainindata.com/
machine-learning data-science python scikit-learn feature-engineering feature-selection feature-extraction

flo7up / relataly-public-python-tutorials
feature-selection,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.
User: flo7up
Home Page: https://www.relataly.com
machine-learning deep-learning time-series-forecasting time-series-prediction recurrent-neural-networks stock-market-prediction twitter-bot churn-prediction keras-tensorflow scikit-learn-python

hannameyer / cast
feature-selection,Developer Version of the R package CAST: Caret Applications for Spatio-Temporal models
User: hannameyer
Home Page: https://hannameyer.github.io/CAST/
caret machine-learning autocorrelation spatial spatio-temporal overfitting feature-selection variable-selection predictive-modeling

hy4m / linket
feature-selection,Everything is Linkable
User: hy4m
correlation feature-selection ggplot2 heatmap r visualization

jalajthanaki / nlpython
feature-selection,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"
User: jalajthanaki
natural-language-processing python-scripting-language deep-learning text-mining parsing part-of-speech feature-engineering feature-extraction feature-selection python2

jaswinder9051998 / zoofs
feature-selection,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.
User: jaswinder9051998
Home Page: https://jaswinder9051998.github.io/zoofs/
machine-learning python evolutionary-algorithms genetic-algorithm feature-selection particle-swarm-optimization particle-swarm grey-wolf-optimizer grey-wolf supervised-learning machine-learning-algorithms machinelearning optimization optimization-algorithms optimization-methods optimization-tools subset-selection

jingweitoo / wrapper-feature-selection-toolbox
feature-selection,This toolbox offers more than 40 wrapper feature selection methods include PSO, GA, DE, ACO, GSA, and etc. They are simple and easy to implement.
User: jingweitoo
machine-learning feature-selection data-mining metaheuristics particle-swarm-optimization genetic-algorithm ant-colony-optimization differential-evolution grey-wolf-optimizer whale-optimization-algorithm

jingweitoo / wrapper-feature-selection-toolbox-python
feature-selection,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.
User: jingweitoo
whale-optimization-algorithm particle-swarm-optimization genetic-algorithm differential-evolution salp-swarm-algorithm grey-wolf-optimizer sine-cosine-algorithm wrapper feature-selection classification

kaushalshetty / featureselectionga
feature-selection,Feature Selection using Genetic Algorithm (DEAP Framework)
User: kaushalshetty
deap feature-selection genetic-algorithm machine-learning python

lastancientone / deep_learning_machine_learning_stock
feature-selection,Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.
User: lastancientone
deep-learning machine-learning stock-price-prediction features-extraction financial-engineering prediction feature-engineering feature-extraction feature-selection stock-data

mfbalin / concrete-autoencoders
feature-selection,
User: mfbalin
machine-learning unsupervised-learning feature-selection concrete-autoencoders icml-2019 icml supervised-learning

microsoft / finnts
feature-selection,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.
Organization: microsoft
Home Page: https://microsoft.github.io/finnts
time-series forecasting machine-learning data-science finnts finance business microsoft r r-package

mlr-org / mlr
feature-selection,Machine Learning in R
Organization: mlr-org
Home Page: https://mlr.mlr-org.com
machine-learning data-science tuning cran r-package predictive-modeling classification regression statistics r

nvidia-merlin / nvtabular
feature-selection,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.
Organization: nvidia-merlin
deep-learning feature-engineering feature-selection gpu machine-learning nvidia preprocessing recommendation-system recommender-system

predict-idlab / powershap
feature-selection,A power-full Shapley feature selection method.
Organization: predict-idlab
feature-selection machine-learning data-science shap

rasgointelligence / feature-engineering-tutorials
feature-selection,Data Science Feature Engineering and Selection Tutorials
Organization: rasgointelligence
Home Page: https://www.rasgoml.com/
notebook tutorials tutorial python pandas data-science machine-learning scikit-learn feature-engineering feature-selection

renatoosousa / geneticalgorithmforfeatureselection
feature-selection,Search the best feature subset for you classification mode
User: renatoosousa
genetic-algorithm feature-selection evolutionary-algorithms evolutionary-algorithm genetic-optimization-algorithm machine-learning machinelearning classifier genetic-programming genetic-algorithm-framework

riken-aip / pyhsiclasso
feature-selection,Versatile Nonlinear Feature Selection Algorithm for High-dimensional Data
Organization: riken-aip
feature-selection feature-extraction machine-learning-algorithms nonlinear python blackbox-algorithm

rodrigo-arenas / sklearn-genetic-opt
feature-selection,ML hyperparameters tuning and features selection, using evolutionary algorithms.
User: rodrigo-arenas
Home Page: https://sklearn-genetic-opt.readthedocs.io
python scikit-learn machine-learning artificial-intelligence hyperparameters deap looking-for-contributors model-selection hyperparameter-optimization automl

rorysroes / sgx-full-orderbook-tick-data-trading-strategy
feature-selection,Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
User: rorysroes
high-frequency-trading limit-order-book python machine-learning feature-selection feature-engineering backtesting-trading-strategies model-selection trading-strategies quantitative-trading

scikit-learn-contrib / stability-selection
feature-selection,scikit-learn compatible implementation of stability selection.
Organization: scikit-learn-contrib
feature-selection machine-learning scikit-learn statistics

smazzanti / mrmr
feature-selection,mRMR (minimum-Redundancy-Maximum-Relevance) for automatic feature selection at scale.
User: smazzanti
machine-learning feature-selection data-science mlops

solegalli / feature-selection-for-machine-learning
feature-selection,Code repository for the online course Feature Selection for Machine Learning
User: solegalli
Home Page: https://www.courses.trainindata.com/p/feature-selection-for-machine-learning
machine-learning data-science feature-selection python

sramirez / spark-infotheoretic-feature-selection
feature-selection,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.
User: sramirez
Home Page: http://sci2s.ugr.es/BigData
mrmr spark brown filter feature-selection

upgini / upgini
feature-selection,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
Organization: upgini
Home Page: https://upgini.com
data-science machine-learning scikit-learn python-library kaggle open-data public-data automl feature-engineering feature-extraction

yimeng-zhang / feature-engineering-and-feature-selection
feature-selection,A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.
User: yimeng-zhang
python machine-learning feature-engineering feature-selection feature-extraction data-mining

yzkang / my-data-competition-experience
feature-selection,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
User: yzkang
machine-learning kaggle-competition data-science tianchi-competition xgboost lightgbm catboost feature-engineering hyperparameter-optimization model-selection