Introduction of sensitivity analysis for randamforest regression, binary classification and multi-class classification of random forest using {forestFloor} package
Introduction of sensitivity analysis for randamforest regression, binary classification and multi-class classification of random forest using {forestFloor} package
Imputation of Missing Values using Random ForestSatoshi Kato
missForest packageの紹介
“MissForest - nonparametric missing value imputation for mixed-type data (DJ Stekhoven, P Bühlmann (2011), Bioinformatics 28 (1), 112-118)
* Satoshi Hara and Kohei Hayashi. Making Tree Ensembles Interpretable: A Bayesian Model Selection Approach. AISTATS'18 (to appear).
arXiv ver.: https://arxiv.org/abs/1606.09066#
* GitHub
https://github.com/sato9hara/defragTrees
Introduction of "the alternate features search" using RSatoshi Kato
Introduction of the alternate features search using R, proposed in the paper. S. Hara, T. Maehara, Finding Alternate Features in Lasso, 1611.05940, 2016.
Imputation of Missing Values using Random ForestSatoshi Kato
missForest packageの紹介
“MissForest - nonparametric missing value imputation for mixed-type data (DJ Stekhoven, P Bühlmann (2011), Bioinformatics 28 (1), 112-118)
* Satoshi Hara and Kohei Hayashi. Making Tree Ensembles Interpretable: A Bayesian Model Selection Approach. AISTATS'18 (to appear).
arXiv ver.: https://arxiv.org/abs/1606.09066#
* GitHub
https://github.com/sato9hara/defragTrees
Introduction of "the alternate features search" using RSatoshi Kato
Introduction of the alternate features search using R, proposed in the paper. S. Hara, T. Maehara, Finding Alternate Features in Lasso, 1611.05940, 2016.
Westminster Communities of Florida's 2016 Volunteers and Employees of the YearWes Meltzer
Westminster Communities of Florida honors our Employees of the Year and Volunteers of the Year each year. This year, at the 19th Annual Awards Banquet, we honor volunteers and employees from around the state. We are so thankful for them.
How to generate PowerPoint slides Non-manually using RSatoshi Kato
Introduction to:
- Basic idea and procedure of {officer} package
- Getting started: Embedding texts, tables and figures in slides
- PowerPoint Structure: Layouts and Placeholders
- Making a template for specific layouts
- Making a template for your own slide-layouts
Resources are avail at: https://github.com/katokohaku/powerpoint_with_officer
Exploratory data analysis using xgboost package in RSatoshi Kato
Explain HOW-TO procedure exploratory data analysis using xgboost (EDAXGB), such as feature importance, sensitivity analysis, feature contribution and feature interaction. It is just based on using built-in predict() function in R package.
All of the sample codes are available at: https://github.com/katokohaku/EDAxgboost
a Japanese introduction of an R package {featuretweakR }
available from: https://github.com/katokohaku/featureTweakR
reference: "Interpretable Predictions of Tree-based Ensembles via Actionable Feature Tweaking" (https://arxiv.org/abs/1706.06691). Codes are at my Github (https://github.com/katokohaku/feature_tweaking)
Outline of Genetic Algorithm + Searching for Maximum Value of Function and Traveling Salesman Problem using R.
To view source codes and animation:
Searching for Maximum Value of Function
- https://github.com/katokohaku/evolutional_comptutation/blob/master/chap2.1.Rmd
Traveling Salesman Problem
- https://github.com/katokohaku/evolutional_comptutation/blob/master/chap2.2.Rmd
Intoroduction & R implementation of "Interpretable predictions of tree-based ...Satoshi Kato
a Japanese introduction and an R implementation of "Interpretable Predictions of Tree-based Ensembles via Actionable Feature Tweaking" (https://arxiv.org/abs/1706.06691). Codes are at my Github (https://github.com/katokohaku/feature_tweaking)