pyHSICLassoVersatile Nonlinear Feature Selection Algorithm for High-dimensional Data
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TextFeatureSelectionPython 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
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dominance-analysisThis 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.
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NVTabularNVTabular 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.
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exemplary-ml-pipelineExemplary, annotated machine learning pipeline for any tabular data problem.
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mrmrmRMR (minimum-Redundancy-Maximum-Relevance) for automatic feature selection at scale.
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msdaLibrary 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
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L0LearnEfficient Algorithms for L0 Regularized Learning
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BallStatistical Inference and Sure Independence Screening via Ball Statistics
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skrobotskrobot is a Python module for designing, running and tracking Machine Learning experiments / tasks. It is built on top of scikit-learn framework.
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bessBest Subset Selection algorithm for Regression, Classification, Count, Survival analysis
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tsa4R code for Time Series Analysis and Its Applications, Ed 4
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FIFA-2019-AnalysisThis is a project based on the FIFA World Cup 2019 and Analyzes the Performance and Efficiency of Teams, Players, Countries and other related things using Data Analysis and Data Visualizations
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fsfcFeature Selection for Clustering
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MlrMachine Learning in R
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feature engineFeature engineering package with sklearn like functionality
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adaptAwesome Domain Adaptation Python Toolbox
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GPScode for "A global pathway selection algorithm for the reduction of detailed chemical kinetic mechanisms" (Gao et al., CNF'16)
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PyImpetusPyImpetus 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
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arfsAll Relevant Feature Selection
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stgPython/R library for feature selection in neural nets. ("Feature selection using Stochastic Gates", ICML 2020)
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featurewizUse advanced feature engineering strategies and select best features from your data set with a single line of code.
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Market-Mix-ModelingMarket Mix Modelling for an eCommerce firm to estimate the impact of various marketing levers on sales
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zoofszoofs 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.
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CASTDeveloper Version of the R package CAST: Caret Applications for Spatio-Temporal models
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FEASTA FEAture Selection Toolbox for C/C+, Java, and Matlab/Octave.
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laravel-rolloutA package to integrate rollout into your Laravel project.
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MissingnoMissing data visualization module for Python.
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Robust-Deep-Learning-PipelineDeep Convolutional Bidirectional LSTM for Complex Activity Recognition with Missing Data. Human Activity Recognition Challenge. Springer SIST (2020)
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TotalLeastSquares.jlSolve many kinds of least-squares and matrix-recovery problems
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adenineADENINE: A Data ExploratioN PipelINE
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missComparemissCompare R package - intuitive missing data imputation framework
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