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Projects in Awesome Lists tagged with variable-importance

A curated list of projects in awesome lists tagged with variable-importance .

https://github.com/ck37/varimpact

Variable importance through targeted causal inference, with Alan Hubbard

causal-inference cv-tmle observational-study targeted-learning tmle variable-importance

Last synced: 26 Apr 2025

https://github.com/mlr-org/mlr3filters

Filter-based feature selection for mlr3

feature-selection filter filters mlr mlr3 r r-package variable-importance

Last synced: 09 Apr 2025

https://github.com/nhejazi/txshift

:package: :game_die: R/txshift: Efficient Estimation of the Causal Effects of Stochastic Interventions, with Corrections for Outcome-Dependent Sampling

causal-effects causal-inference censored-data machine-learning robust-statistics statistics stochastic-interventions stochastic-treatment-regimes targeted-learning treatment-effects variable-importance

Last synced: 16 Dec 2024

https://github.com/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.

breast-cancer-prediction cancer-data decision-trees machine-learning prediction-model survival-analysis variable-importance

Last synced: 20 Nov 2024

https://github.com/insightsengineering/unihtee

Tools for uncovering treatment effect modifiers in high-dimensional data.

heterogeneous-treatment-effects high-dimensional-data nonparametrics targeted-learning variable-importance

Last synced: 10 Apr 2025

https://github.com/erikerlandson/1-pass-data-science

Demo notebook and data for Spark Summit Dublin 2017: One-Pass Data Science with Generative T-Digests

apache-spark feature-importance jupyter jupyter-notebook pyspark python t-digest variable-importance

Last synced: 24 Feb 2025

https://github.com/nhejazi/talk_txshift

:speech_balloon: Talk on causal inference and variable importance with stochastic interventions under two-phase sampling

causal-inference censored-data inverse-probability-weights machine-learning marginal-structural-models stochastic-interventions targeted-learning variable-importance

Last synced: 03 Apr 2025

https://github.com/erikerlandson/1-pass-variable-importance

Demo of 1-pass variable importance using t-digests

apache-spark scala t-digest variable-importance

Last synced: 24 Feb 2025

https://github.com/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.

3d-printing labelencoder matplotlib numpy pandas principal-component-analysis sklearn-library sqlalchemy standardization variable-importance

Last synced: 28 Mar 2025

https://github.com/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.

agglomerative-algorithm bootstrap-sampling classification clustering cross-validation data-cleaning decision-tree hierarchical-clustering model-evaluation model-interpretation predictive-analytics r random-forest silhouette-analysis statistics support-vector-machine variable-importance

Last synced: 02 Mar 2025