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.
high-frequency-trading limit-order-book python machine-learning feature-selection feature-engineering backtesting-trading-strategies model-selection trading-strategies quantitative-trading algorithmic-trading investment orderbook-tick-data quant trading market-making market-maker market-microstructure orderbook
Language:Jupyter Notebook 1792
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 1773
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 1730
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 1627
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 1291
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.
deep-learning machine-learning stock-price-prediction features-extraction financial-engineering prediction feature-engineering feature-extraction feature-selection stock-data stock-trading stock-analysis stock-prices stock-market stock-prediction algorithms data-science trading technical-analysis neural-network
Language:Jupyter Notebook 1139
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 1004
aerdem4 / lofo-importance
Leave One Feature Out Importance
feature-importance machine-learning data-science feature-selection explainable-ai
Language:Python 796
evalml
alteryx / evalml
EvalML is an AutoML library written in python.
automl machine-learning data-science model-selection hyperparameter-tuning optimization feature-engineering feature-selection
Language:Python 708
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 661
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.
data-analysis data-mining data-science data-scientists data-visualization deep-learning feature-engineering feature-extraction feature-scaling feature-selection features machine-learning scikit-learn
Language:Jupyter Notebook 584
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
Language:Python 538
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 530
klib
akanz1 / klib
Easy to use Python library of customized functions for cleaning and analyzing data.
data-science data-analysis klib data-visualization python feature-selection data-cleaning data-preprocessing
Language:Python 475
cod3licious / autofeat
Linear Prediction Model with Automated Feature Engineering and Selection Capabilities
automated-data-science automated-feature-engineering automated-machine-learning automl feature-engineering feature-selection linear-regression machine-learning machine-learning-models
Language:Python 474
smazzanti / mrmr
mRMR (minimum-Redundancy-Maximum-Relevance) for automatic feature selection at scale.
data-science feature-selection machine-learning mlops
Language:Python 460
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++ 422
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 397
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 380
anujdutt9 / Feature-Selection-for-Machine-Learning
Methods with examples for Feature Selection during Pre-processing in Machine Learning.
correlation feature-selection machine-learning python36
Language:Jupyter Notebook 357
kaushalshetty / FeatureSelectionGA
Feature Selection using Genetic Algorithm (DEAP Framework)
deap feature-selection genetic-algorithm machine-learning python
Language:Python 344
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"
natural-language-processing python-scripting-language deep-learning text-mining parsing part-of-speech feature-engineering feature-extraction feature-selection python2
Language:Jupyter Notebook 316
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 288
rodrigo-arenas / Sklearn-genetic-opt
ML hyperparameters tuning and features selection, using evolutionary algorithms.
python scikit-learn machine-learning artificial-intelligence hyperparameters deap looking-for-contributors model-selection hyperparameter-optimization automl begginer-friendly evolutionary-algorithms contributions-welcome help-wanted good-first-issue goodfirstissue sklearn up-for-grabs featureselection feature-selection
Language:Python 272
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 271
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 267
rasgointelligence / feature-engineering-tutorials
Data Science Feature Engineering and Selection Tutorials
data-cleaning data-science exploratory-data-analysis feature-engineering feature-selection features jupyter machine-learning notebook pandas pandas-profiling pyrasgo python scikit-learn sweetviz tutorial tutorials xgboost
Language:Jupyter Notebook 263
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 235
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 226
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 224
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 211
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 208
scikit-learn-contrib / stability-selection
scikit-learn compatible implementation of stability selection.
feature-selection machine-learning scikit-learn statistics
Language:Python 208
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 207
predict-idlab / powershap
A power-full Shapley feature selection method.
data-science feature-selection machine-learning shap
Language:Python 174
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 data-science finnts finance business microsoft r r-package rstats feature-selection
Language:R 172

feature-selection

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

edyoda / data-science-complete-tutorial

feature-engine / feature_engine

mlr-org / mlr

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

LastAncientOne / Deep_Learning_Machine_Learning_Stock

NVIDIA-Merlin / NVTabular

aerdem4 / lofo-importance

alteryx / evalml

duxuhao / Feature-Selection

ashishpatel26 / Amazing-Feature-Engineering

AutoViML / featurewiz

cerlymarco / shap-hypetune

akanz1 / klib

cod3licious / autofeat

smazzanti / mrmr

abess-team / abess

EpistasisLab / scikit-rebate

yzkang / My-Data-Competition-Experience

anujdutt9 / Feature-Selection-for-Machine-Learning

kaushalshetty / FeatureSelectionGA

jalajthanaki / NLPython

upgini / upgini

rodrigo-arenas / Sklearn-genetic-opt

adapt-python / adapt

solegalli / feature-selection-for-machine-learning

rasgointelligence / feature-engineering-tutorials

jaswinder9051998 / zoofs

CynthiaKoopman / Network-Intrusion-Detection

JingweiToo / Wrapper-Feature-Selection-Toolbox-Python

arnaldog12 / Machine_Learning

chasedehan / BoostARoota

scikit-learn-contrib / stability-selection

danyalimran93 / Music-Emotion-Recognition

predict-idlab / powershap

microsoft / finnts