feature-selection

There are 42 repositories under feature-selection topic.

rorysroes / SGX-Full-OrderBook-Tick-Data-Trading-Strategy
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
algorithmic-trading backtesting-trading-strategies feature-engineering feature-selection high-frequency-trading investment limit-order-book machine-learning market-maker market-making market-microstructure model-selection orderbook orderbook-tick-data python quant quantitative-trading trading trading-strategies
Language:Jupyter Notebook 2161
feature_engine
feature-engine / feature_engine
Feature engineering package with sklearn like functionality
machine-learning data-science python scikit-learn feature-engineering feature-selection feature-extraction
Language:Python 2159
edyoda / data-science-complete-tutorial
For extensive instructor led learning
machine-learning scikit-learn linear-regression nearest-neighbors feature-selection decision-trees numpy pandas pipeline
Language:Jupyter Notebook 1816
LastAncientOne / Deep_Learning_Machine_Learning_Stock
Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.
algorithms data-science deep-learning feature-engineering feature-extraction feature-selection features-extraction financial-engineering machine-learning neural-network prediction stock-analysis stock-data stock-market stock-prediction stock-price-prediction stock-prices stock-trading technical-analysis trading
Language:Jupyter Notebook 1669
mlr-org / mlr
Machine Learning in R
machine-learning data-science tuning cran r-package predictive-modeling classification regression statistics r survival-analysis imbalance-correction tutorial mlr learners hyperparameters-optimization feature-selection multilabel-classification clustering stacking
Language:R 1669
Yimeng-Zhang / feature-engineering-and-feature-selection
A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.
data-mining feature-engineering feature-extraction feature-selection machine-learning python
Language:Jupyter Notebook 1615
NVIDIA-Merlin / NVTabular
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.
deep-learning feature-engineering feature-selection gpu machine-learning nvidia preprocessing recommendation-system recommender-system
Language:Python 1126
aerdem4 / lofo-importance
Leave One Feature Out Importance
data-science explainable-ai feature-importance feature-selection machine-learning
Language:Python 849
evalml
alteryx / evalml
EvalML is an AutoML library written in python.
automl data-science feature-engineering feature-selection hyperparameter-tuning machine-learning model-selection optimization
Language:Python 833
ashishpatel26 / Amazing-Feature-Engineering
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-engineering machine-learning deep-learning scikit-learn data-mining data-science data-scientists feature-scaling feature-extraction feature-selection features data-analysis data-visualization
Language:Jupyter Notebook 750
duxuhao / Feature-Selection
Features selector based on the self selected-algorithm, loss function and validation method
machine-learning feature-engineering feature-selection data-science greedy-search feature-importance feature-extraction
Language:Python 681
AutoViML / featurewiz
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.
feature-engineering categorical-variables best-encoders feature-engg rfe rfecv feature-extraction feature-selection featuretools xgboost autoencoders feature-encoding mrmr
Language:Python 673
smazzanti / mrmr
mRMR (minimum-Redundancy-Maximum-Relevance) for automatic feature selection at scale.
machine-learning feature-selection data-science mlops
Language:Python 615
cerlymarco / shap-hypetune
A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.
parameter-tuning hyperparameter-optimization feature-selection model-selection xgboost lightgbm shap
Language:Jupyter Notebook 580
cod3licious / autofeat
Linear Prediction Model with Automated Feature Engineering and Selection Capabilities
machine-learning machine-learning-models linear-regression feature-engineering feature-selection automl automated-machine-learning automated-feature-engineering automated-data-science
Language:Python 529
klib
akanz1 / klib
Easy to use Python library of customized functions for cleaning and analyzing data.
data-analysis data-cleaning data-preprocessing data-science data-visualization feature-selection klib python
Language:Python 521
abess
abess-team / abess
Fast Best-Subset Selection Library
polynomial-algorithm high-dimensional-data best-subset-selection machine-learning python r scikit-learn principal-component-analysis linear-regression classification-algorithm cox-regression logistic-regression multitask-learning ordinal-regression poisson-regression robust-principal-component-analysis sparse-principal-component-analysis feature-selection sure-independence-screening
Language:C++ 489
desbordante-core
Desbordante / desbordante-core
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.
data-analytics data-cleaning data-cleansing data-engineering data-exploration data-mining data-profiling data-science data-wrangling data-preprocessing feature-selection feature-engineering feature-extraction spreadsheets tabular-data anomaly-detection data-mining-algorithms exploratory-data-analysis knowledge-discovery correlations
Language:C++ 429
EpistasisLab / scikit-rebate
A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.
data-science feature-selection python
Language:Python 420
yzkang / My-Data-Competition-Experience
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
machine-learning kaggle-competition data-science tianchi-competition xgboost lightgbm catboost feature-engineering hyperparameter-optimization model-selection feature-selection model-fusion automl sql python deep-learning gan
Language:Python 398
kaushalshetty / FeatureSelectionGA
Feature Selection using Genetic Algorithm (DEAP Framework)
feature-selection genetic-algorithm deap machine-learning python
Language:Python 371
anujdutt9 / Feature-Selection-for-Machine-Learning
Methods with examples for Feature Selection during Pre-processing in Machine Learning.
feature-selection machine-learning python36 correlation
Language:Jupyter Notebook 364
adapt-python / adapt
Awesome Domain Adaptation Python Toolbox
domain-adaptation transfer-learning few-shot-learning zero-shot-learning adversarial-learning adversarial-networks feature-selection importance-sampling regularization-parameters machine-learning deep-learning generalization python tensorflow scikit-learn dann
Language:Python 356
rodrigo-arenas / Sklearn-genetic-opt
ML hyperparameters tuning and features selection, using evolutionary algorithms.
artificial-intelligence automl begginer-friendly contributions-welcome deap evolutionary-algorithms feature-selection featureselection good-first-issue goodfirstissue help-wanted hyperparameter-optimization hyperparameters looking-for-contributors machine-learning model-selection python scikit-learn sklearn up-for-grabs
Language:Python 350
upgini / upgini
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
data-science machine-learning scikit-learn python-library kaggle open-data public-data automl feature-engineering feature-extraction feature-selection features kaggle-solution data-enrichment automated-feature-engineering open-datasets automl-pipeline large-language-models chatgpt llm
Language:Python 349
feature-selection-for-machine-learning
solegalli / feature-selection-for-machine-learning
Code repository for the online course Feature Selection for Machine Learning
data-science feature-selection machine-learning python
Language:Jupyter Notebook 334
jalajthanaki / NLPython
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"
deep-learning feature-engineering feature-extraction feature-selection natural-language-processing parsing part-of-speech python-scripting-language python2 text-mining
Language:Jupyter Notebook 324
rasgointelligence / feature-engineering-tutorials
Data Science Feature Engineering and Selection Tutorials
notebook tutorials tutorial python pandas data-science machine-learning scikit-learn feature-engineering feature-selection features xgboost pandas-profiling sweetviz pyrasgo jupyter exploratory-data-analysis data-cleaning
Language:Jupyter Notebook 288
JingweiToo / Wrapper-Feature-Selection-Toolbox-Python
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.
whale-optimization-algorithm particle-swarm-optimization genetic-algorithm differential-evolution salp-swarm-algorithm grey-wolf-optimizer sine-cosine-algorithm wrapper feature-selection classification machine-learning data-mining harris-hawks-optimization bat-algorithm firefly-algorithm flower-pollination-algorithm cuckoo-search
Language:Python 281
CynthiaKoopman / Network-Intrusion-Detection
Machine Learning with the NSL-KDD dataset for Network Intrusion Detection
nsl-kdd datamining feature-selection network-intrusion-detection intrusion-detection-system machine-learning kdd99 decision-trees random-forest cross-validation
Language:Jupyter Notebook 269
zoofs
jaswinder9051998 / zoofs
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.
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
Language:Python 250
danyalimran93 / Music-Emotion-Recognition
A Machine Learning Approach of Emotional Model
machine-learning data-science feature-extraction feature-selection feature-scaling music-information-retrieval digital-signal-processing librosa
Language:Python 246
microsoft / finnts
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.
time-series forecasting machine-learning finnts finance business microsoft r r-package rstats feature-selection agent ai llm
Language:R 228
chasedehan / BoostARoota
A fast xgboost feature selection algorithm
machine-learning machine-learning-algorithms feature-selection xgboost-algorithm xgboost dimension-reduction algorithm boruta data-science datascientist datascience machinelearning
Language:Python 227
arnaldog12 / Machine_Learning
Estudo e implementação dos principais algoritmos de Machine Learning em Jupyter Notebooks.
machine-learning machine-learning-algorithms adaboost decision-trees kmeans knn linear-discriminant-analysis principal-component-analysis naive-bayes regression linear-regression neural-network redes-neurais-artificiais multilinear-regression polynomial-regression python feature-selection logistic-regression
Language:Jupyter Notebook 224
scikit-learn-contrib / stability-selection
scikit-learn compatible implementation of stability selection.
feature-selection machine-learning scikit-learn statistics
Language:Python 214

feature-selection

rorysroes / SGX-Full-OrderBook-Tick-Data-Trading-Strategy

feature-engine / feature_engine

edyoda / data-science-complete-tutorial

LastAncientOne / Deep_Learning_Machine_Learning_Stock

mlr-org / mlr

Yimeng-Zhang / feature-engineering-and-feature-selection

NVIDIA-Merlin / NVTabular

aerdem4 / lofo-importance

alteryx / evalml

ashishpatel26 / Amazing-Feature-Engineering

duxuhao / Feature-Selection

AutoViML / featurewiz

smazzanti / mrmr

cerlymarco / shap-hypetune

cod3licious / autofeat

akanz1 / klib

abess-team / abess

Desbordante / desbordante-core

EpistasisLab / scikit-rebate

yzkang / My-Data-Competition-Experience

kaushalshetty / FeatureSelectionGA

anujdutt9 / Feature-Selection-for-Machine-Learning

adapt-python / adapt

rodrigo-arenas / Sklearn-genetic-opt

upgini / upgini

solegalli / feature-selection-for-machine-learning

jalajthanaki / NLPython

rasgointelligence / feature-engineering-tutorials

JingweiToo / Wrapper-Feature-Selection-Toolbox-Python

CynthiaKoopman / Network-Intrusion-Detection

jaswinder9051998 / zoofs

danyalimran93 / Music-Emotion-Recognition

microsoft / finnts

chasedehan / BoostARoota

arnaldog12 / Machine_Learning

scikit-learn-contrib / stability-selection