GitHub topics: variable-importance
bgreenwell/fastshap
Fast approximate Shapley values in R
Language: R - Size: 99.4 MB - Last synced at: about 7 hours ago - Pushed at: about 1 year ago - Stars: 121 - Forks: 18
MI2DataLab/survshap
SurvSHAP(t): Time-dependent explanations of machine learning survival models
Language: Jupyter Notebook - Size: 8.99 MB - Last synced at: 20 days ago - Pushed at: over 1 year ago - Stars: 85 - Forks: 16
ModelOriented/survex
Explainable Machine Learning in Survival Analysis
Language: R - Size: 309 MB - Last synced at: 9 days ago - Pushed at: 11 months ago - Stars: 111 - Forks: 10
bdwilliamson/vimp
Perform inference on algorithm-agnostic variable importance
Language: R - Size: 14.1 MB - Last synced at: about 1 month ago - Pushed at: 3 months ago - Stars: 24 - Forks: 8
tlverse/tmle3
π―π Generalized Targeted Learning Framework
Language: R - Size: 1.14 MB - Last synced at: about 2 months ago - Pushed at: 6 months ago - Stars: 38 - Forks: 14
Baschin1103/Principal_component_analysis
In this repository you find a python program and the prints and 3D-visualization of it. After the KNN-Classification I wanted to know which variables have the most relevance for the results. One approach for this is the Principal-Component-Analysis (PCA). More details in the python program as comments.
Language: Python - Size: 136 KB - Last synced at: about 2 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0
mlr-org/mlr3filters
Filter-based feature selection for mlr3
Language: R - Size: 11.1 MB - Last synced at: 4 days ago - Pushed at: 4 months ago - Stars: 20 - Forks: 8
nhejazi/txshift
:package: R/txshift: Efficient Estimation of the Causal Effects of Stochastic Interventions, with Corrections for Outcome-Dependent Sampling
Language: R - Size: 2.32 MB - Last synced at: about 18 hours ago - Pushed at: 8 months ago - Stars: 14 - Forks: 5
blind-contours/SuperNOVA
:dizzy: :dart: Automatic identification of variable and interaction importance using basis functions and non-parametric estimation of interactions/effect modification using joint stochastic interventions.
Language: R - Size: 193 MB - Last synced at: about 18 hours ago - Pushed at: over 1 year ago - Stars: 9 - Forks: 1
tlverse/tmle3_lecture π¦
π―π An introductory workshop lecture on a generalized framework for Targeted Learning using the tmle3 R package
Language: JavaScript - Size: 839 KB - Last synced at: about 2 months ago - Pushed at: about 7 years ago - Stars: 3 - Forks: 0
tlverse/tmle3mopttx
π― π― Targeted Learning and Variable Importance for the Causal Effect of an Optimal Individualized Treatment Intervention
Language: R - Size: 1.39 MB - Last synced at: about 2 months ago - Pushed at: almost 3 years ago - Stars: 12 - Forks: 3
roland045/flyball_race_analysis
Analysis of dog racing data to improve team performance
Language: Jupyter Notebook - Size: 6.86 MB - Last synced at: about 1 month ago - Pushed at: 5 months ago - Stars: 2 - Forks: 0
koalaverse/vip
Variable Importance Plots (VIPs)
Language: R - Size: 407 MB - Last synced at: 8 days ago - Pushed at: over 1 year ago - Stars: 187 - Forks: 24
MoganaD/Machine-Learning-on-Breast-Cancer-Survival-Prediction
We used different machine learning approaches to build models for detecting and visualizing important prognostic indicators of breast cancer survival rate. This repository contains R source codes for 5 steps which are, model evaluation, Random Forest further modelling, variable importance, decision tree and survival analysis. These can be a pipeline for researcher who are interested to conduct studies on survival prediction of any type of cancers using multi model data.
Language: R - Size: 253 KB - Last synced at: 6 months ago - Pushed at: over 4 years ago - Stars: 12 - Forks: 7
jluchman/domir
Tools to Support Relative Importance Analysis
Language: R - Size: 4.61 MB - Last synced at: 3 days ago - Pushed at: 3 days ago - Stars: 5 - Forks: 3
hofnerb/stabs
Stability Selection with Error Control
Language: R - Size: 820 KB - Last synced at: about 1 month ago - Pushed at: over 4 years ago - Stars: 26 - Forks: 9
antononcube/WL-VariableImportanceByClassifiers-paclet
WL paclet with functions for finding variables importance in datasets.
Language: Mathematica - Size: 399 KB - Last synced at: about 1 month ago - Pushed at: 9 months ago - Stars: 0 - Forks: 0
blind-contours/CVtreeMLE
:deciduous_tree: :dart: Cross Validated Decision Trees with Targeted Maximum Likelihood Estimation
Language: R - Size: 127 MB - Last synced at: about 17 hours ago - Pushed at: 11 months ago - Stars: 5 - Forks: 2
marinavillaschi/equipment-failure-prediction
Prediction of equipment failures
Language: Jupyter Notebook - Size: 854 KB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0
Scrayil/Air-Quality-Prediction
The aim of this project is to develop a machine learning model to predict the levels of CO in the air using historical datasets containing atmospheric variables. The project makes use of variables selection, decision trees, and cross-validation techniques to ensure robustness and model accuracy.
Language: R - Size: 2.12 MB - Last synced at: 12 months ago - Pushed at: 12 months ago - Stars: 0 - Forks: 0
PiotrTymoszuk/clustTools
Comprehensive dimensionality reduction and cluster analysis toolset
Language: R - Size: 392 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0
ck37/varimpact
Variable importance through targeted causal inference, with Alan Hubbard
Language: R - Size: 618 KB - Last synced at: 19 days ago - Pushed at: about 2 years ago - Stars: 57 - Forks: 12
Lefteris-Souflas/Election-Classification-and-Clustering-Analysis
Creating predictive models to classify Trump's vote share and clustering counties based on demographics and economic variables. Report findings in PDF with detailed methodologies, model assessments, and R code for the project.
Language: R - Size: 587 KB - Last synced at: 2 months ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0
Arthur-Provost/WSL_Bern_fire_susceptibility
This project relates to a methodological report on canton Bern forest fire modelling and mitigation strategies.
Language: R - Size: 84 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0
shinho123/K-Artificial-Intelligence-Electronic-Manufacturing-Data-Analysis-Competition-plating-process-
2022λ 2νκΈ° ν νλ‘μ νΈ : λκΈκ³΅μ λ°μ΄ν° μ λΆμ(k-μΈκ³΅μ§λ₯ μ μ‘°λ°μ΄ν° λΆμ κ²½μ§λν)
Language: Jupyter Notebook - Size: 2.21 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 0
bdwilliamson/vimpy
Perform inference on algorithm-agnostic variable importance in Python
Language: Python - Size: 407 KB - Last synced at: 9 days ago - Pushed at: about 3 years ago - Stars: 20 - Forks: 5
bdwilliamson/spvim_supplementary π¦
Reproduce analyses from "Efficient nonparametric statistical inference on population feature importance using Shapley values"
Language: Python - Size: 929 KB - Last synced at: 7 months ago - Pushed at: almost 5 years ago - Stars: 5 - Forks: 1
isarn/isarn-sketches-spark
Routines and data structures for using isarn-sketches idiomatically in Apache Spark
Language: Scala - Size: 1.33 MB - Last synced at: about 1 month ago - Pushed at: 12 months ago - Stars: 29 - Forks: 12
lcrawlab/GOALS
Code and tutorials for implementing the GlObal And Local Score
Language: R - Size: 1.17 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0
mztrk/ImportantVariables
Important Variable selection
Size: 2.93 KB - Last synced at: over 1 year ago - Pushed at: almost 6 years ago - Stars: 1 - Forks: 0
erikerlandson/1-pass-variable-importance
Demo of 1-pass variable importance using t-digests
Language: Jupyter Notebook - Size: 13.7 KB - Last synced at: 3 months ago - Pushed at: almost 8 years ago - Stars: 1 - Forks: 0
erikerlandson/1-pass-data-science
Demo notebook and data for Spark Summit Dublin 2017: One-Pass Data Science with Generative T-Digests
Language: Jupyter Notebook - Size: 34.4 MB - Last synced at: 3 months ago - Pushed at: over 7 years ago - Stars: 1 - Forks: 0
kdis-lab/Early_readmission_diabetic_patients
A large dataset for studying the early readmission of diabetic patients problem
Language: R - Size: 24.8 MB - Last synced at: over 1 year ago - Pushed at: over 5 years ago - Stars: 0 - Forks: 0
nhejazi/methyvim π¦
:package: :microscope: R/methyvim: Targeted, Robust, and Model-free Differential Methylation Analysis
Language: TeX - Size: 4.99 MB - Last synced at: almost 2 years ago - Pushed at: about 5 years ago - Stars: 3 - Forks: 0
tlverse/tmle3shift
π― :game_die: Targeted Learning of the Causal Effects of Stochastic Interventions
Language: R - Size: 472 KB - Last synced at: about 1 year ago - Pushed at: over 2 years ago - Stars: 14 - Forks: 1
S-CHAN11/Insurance-Claim-Prediction
In this project, I use 3 machine learning models (CART, Random Forest and ANN) to predict the claim frequency for a travel insurance firm. I also evaluate which of the three models is most suitable for our dataset.
Language: Jupyter Notebook - Size: 1.91 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0
sushrutshitoot/Housing-Market-Price-Prediction
Build a predictive model for the sale prices of homes in a city and explore potential equity issues with the real-estate assessment process
Language: R - Size: 15.1 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0
andremonaco/Xy
Simulating Supervised Learning Data
Language: R - Size: 4.84 MB - Last synced at: almost 2 years ago - Pushed at: about 2 years ago - Stars: 8 - Forks: 6
lorinanthony/RATE
Code for Variable Selection in Black Box Methods with RelATive cEntrality (RATE) Measures
Language: Jupyter Notebook - Size: 20.7 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 17 - Forks: 4
sestelo/fwdselect
An R package for selecting variables in regression models
Language: R - Size: 188 KB - Last synced at: about 1 year ago - Pushed at: over 9 years ago - Stars: 1 - Forks: 1
majianthu/aps2020
Code for the paper 'Variable Selection with Copula Entropy' published on Chinese Journal of Applied Probability and Statistics
Language: R - Size: 86.9 KB - Last synced at: about 2 years ago - Pushed at: about 3 years ago - Stars: 14 - Forks: 3
MalikHebbat/Thesis---Code
Code for Master Thesis
Language: R - Size: 5.19 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0
S-Soluel/STAT-172-Final-Project
Final Project: Predictive and descriptive analysis, interpretations, and recommendations based on Austin Animal Center data on cats housed at the shelter. The main focus of this analysis is to determine which factors affect a cat's chances of being adopted or returned to their owner.
Language: R - Size: 3.02 MB - Last synced at: almost 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0
eyllcyldrm/MantarSiniflandirma
SVC and KNN methods were used to predict whether mushrooms are poisonous or edible according to their properties. Random forest and chi-square variable selection methods were applied and the 10-fold cross validation method was used and f1 scores were calculated by re-estimating. Finally, the models were compared.
Language: Jupyter Notebook - Size: 108 KB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 0 - Forks: 0
joshloyal/drforest
Dimension Reduction Forests
Language: Jupyter Notebook - Size: 3.1 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 5 - Forks: 1
ModelOriented/vivo
Variable importance via oscillations
Language: R - Size: 5.14 MB - Last synced at: 21 days ago - Pushed at: over 4 years ago - Stars: 14 - Forks: 3
nhejazi/talk_txshift
:speech_balloon: Talk on causal inference and variable importance with stochastic interventions under two-phase sampling
Language: TeX - Size: 4.8 MB - Last synced at: about 1 month ago - Pushed at: 11 months ago - Stars: 1 - Forks: 0
ck37/ppmi-challenge-2016
Parkinson's Progression Marker Initiative data science challenge, 2016
Language: R - Size: 89.8 KB - Last synced at: over 1 year ago - Pushed at: about 8 years ago - Stars: 3 - Forks: 1
alaradirik/variable-selection-using-R
R script to rank and select variables based on their importance/predictive power
Language: R - Size: 35.2 KB - Last synced at: about 2 years ago - Pushed at: almost 6 years ago - Stars: 0 - Forks: 0
andremonaco/xypy
Simulating Supervised Learning Data
Language: Python - Size: 134 KB - Last synced at: 22 days ago - Pushed at: about 6 years ago - Stars: 2 - Forks: 0