abess-team/abess

Fast Best-Subset Selection Library

Language: C++ - Size: 209 MB - Last synced at: about 15 hours ago - Pushed at: 7 days ago - Stars: 485 - Forks: 42

LAMPSPUC/StateSpaceLearning.jl

StateSpaceLearning.jl is a Julia package for time-series analysis using state space learning framework.

Language: Julia - Size: 36.7 MB - Last synced at: 25 days ago - Pushed at: 25 days ago - Stars: 19 - Forks: 2

abess-team/A-Splicing-Approach-to-Best-Subset-of-Groups-Selection

Language: R - Size: 4.9 MB - Last synced at: about 1 month ago - Pushed at: over 2 years ago - Stars: 8 - Forks: 1

abess-team/A-Polynomial-Algorithm-for-Best-Subset-Selection-Problem

Reproducible materials for "A polynomial algorithm for best-subset selection problem"

Language: R - Size: 1.17 MB - Last synced at: about 2 months ago - Pushed at: over 2 years ago - Stars: 6 - Forks: 0

chris-santiago/steps

A SciKit-Learn style feature selector using best subsets and stepwise regression.

Language: Jupyter Notebook - Size: 781 KB - Last synced at: 1 day ago - Pushed at: about 1 year ago - Stars: 5 - Forks: 0

abess-team/abess-A-Fast-Best-Subset-Selection-Library-in-Python-and-R

Reproducible materials for "abess: A Fast Best-Subset Selection Library in Python and R"

Language: Python - Size: 8.03 MB - Last synced at: about 2 months ago - Pushed at: over 2 years ago - Stars: 5 - Forks: 0

mamomen1996/Python_CS_02

Sports Analytics in Python

Language: HTML - Size: 4.73 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 0

mamomen1996/R_CS_04

Sports Analytics in R (Step-wise Regression and Subset Selection Regression)

Language: HTML - Size: 983 KB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 0

Hadley-Dixon/DiabetesRegression

A MLR algorithm that analyzes diabetes data in African Americans to find factors predicting diagnosis

Language: HTML - Size: 3.36 MB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0

rmead7/Aerial-Biomass-Production

Linear Regression to identify the important physicochemical properties of the substrate that influence the aerial biomass production in the Cape Fear Estuary.

Language: R - Size: 248 KB - Last synced at: almost 2 years ago - Pushed at: almost 3 years ago - Stars: 0 - Forks: 0