狠狠撸shows by User: kato

狠狠撸shows by User: kato_kohaku / http://www.slideshare.net/images/logo.gif 狠狠撸shows by User: kato_kohaku / Sat, 04 Apr 2020 01:45:57 GMT 狠狠撸Share feed for 狠狠撸shows by User: kato_kohaku How to generate PowerPoint slides Non-manually using R /slideshow/how-to-generate-powerpoint-slides-nonmanually-using-r/231387408 powerpointwithofficer-200404014557
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 ]]>
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 ]]> Sat, 04 Apr 2020 01:45:57 GMT /slideshow/how-to-generate-powerpoint-slides-nonmanually-using-r/231387408 kato_kohaku@slideshare.net(kato_kohaku) How to generate PowerPoint slides Non-manually using R kato_kohaku 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 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/powerpointwithofficer-200404014557-thumbnail.jpg?width=120&height=120&fit=bounds" /> 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

How to generate PowerPoint slides Non-manually using R from Satoshi Kato

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0 Dimensionality reduction with t-SNE(Rtsne) and UMAP(uwot) using R packages. /slideshow/dimensionality-reduction-with-tsne-and-umap-using-r-176806642/176806642 dimensionalityreductionwithtsneumapusingr-190927154000
All sample codes are available at: https://github.com/katokohaku/tSNE_and_UMAP_using_R_packages]]>
All sample codes are available at: https://github.com/katokohaku/tSNE_and_UMAP_using_R_packages]]> Fri, 27 Sep 2019 15:40:00 GMT /slideshow/dimensionality-reduction-with-tsne-and-umap-using-r-176806642/176806642 kato_kohaku@slideshare.net(kato_kohaku) Dimensionality reduction with t-SNE(Rtsne) and UMAP(uwot) using R packages. kato_kohaku All sample codes are available at: https://github.com/katokohaku/tSNE_and_UMAP_using_R_packages <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/dimensionalityreductionwithtsneumapusingr-190927154000-thumbnail.jpg?width=120&height=120&fit=bounds" /> All sample codes are available at: https://github.com/katokohaku/tSNE_and_UMAP_using_R_packages

Dimensionality reduction with t-SNE(Rtsne) and UMAP(uwot) using R packages. from Satoshi Kato

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0 Exploratory data analysis using xgboost package in R /slideshow/exploratory-data-analysis-using-xgboost-package-in-r-146048320/146048320 exploratorydataanalysisusingxgboost-190516135022
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 ]]>
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 ]]> Thu, 16 May 2019 13:50:22 GMT /slideshow/exploratory-data-analysis-using-xgboost-package-in-r-146048320/146048320 kato_kohaku@slideshare.net(kato_kohaku) Exploratory data analysis using xgboost package in R kato_kohaku 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 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/exploratorydataanalysisusingxgboost-190516135022-thumbnail.jpg?width=120&height=120&fit=bounds" /> 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

Exploratory data analysis using xgboost package in R from Satoshi Kato

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0 How to use in R model-agnostic data explanation with DALEX & iml /slideshow/how-to-use-in-r-modelagnostic-data-explanation-with-dalex-iml/133851953 how-to-use-in-rmodel-agnosticdata-explanation-190301133559
機械学習の説明方法をRで使うためのチュートリアル. DALEXとimlパッケージを紹介します。]]>
機械学習の説明方法をRで使うためのチュートリアル. DALEXとimlパッケージを紹介します。]]> Fri, 01 Mar 2019 13:35:59 GMT /slideshow/how-to-use-in-r-modelagnostic-data-explanation-with-dalex-iml/133851953 kato_kohaku@slideshare.net(kato_kohaku) How to use in R model-agnostic data explanation with DALEX & iml kato_kohaku 機械学習の説明方法をRで使うためのチュートリアル. DALEXとimlパッケージを紹介します。 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/how-to-use-in-rmodel-agnosticdata-explanation-190301133559-thumbnail.jpg?width=120&height=120&fit=bounds" /> 機械学習の説明方法をRで使うためのチュートリアル. DALEXとimlパッケージを紹介します。

How to use in R model-agnostic data explanation with DALEX & iml from Satoshi Kato

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0 Introduction of inspectDF package /slideshow/introduction-of-inspectdf-package/113651757 introductionofinspectdfpackage-180909113110
R package for getting inspected rules as data.frame. Available from: https://github.com/katokohaku/inspectDF ]]>
R package for getting inspected rules as data.frame. Available from: https://github.com/katokohaku/inspectDF ]]> Sun, 09 Sep 2018 11:31:10 GMT /slideshow/introduction-of-inspectdf-package/113651757 kato_kohaku@slideshare.net(kato_kohaku) Introduction of inspectDF package kato_kohaku R package for getting inspected rules as data.frame. Available from: https://github.com/katokohaku/inspectDF <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/introductionofinspectdfpackage-180909113110-thumbnail.jpg?width=120&height=120&fit=bounds" /> R package for getting inspected rules as data.frame. Available from: https://github.com/katokohaku/inspectDF

Introduction of inspectDF package from Satoshi Kato

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0 Introduction of featuretweakR package /slideshow/introduction-of-featuretweakr-package/113651431 introductionoffeaturetweakrpackage-180909112200
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)]]>
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)]]> Sun, 09 Sep 2018 11:22:00 GMT /slideshow/introduction-of-featuretweakr-package/113651431 kato_kohaku@slideshare.net(kato_kohaku) Introduction of featuretweakR package kato_kohaku 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) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/introductionoffeaturetweakrpackage-180909112200-thumbnail.jpg?width=120&height=120&fit=bounds" /> 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)

Introduction of featuretweakR package from Satoshi Kato

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0 Genetic algorithm full scratch with R /slideshow/genetic-algorithm-full-scratch-with-r/111608896 geneticalgorithmfullscratchwithr-180826104320
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]]>
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]]> Sun, 26 Aug 2018 10:43:19 GMT /slideshow/genetic-algorithm-full-scratch-with-r/111608896 kato_kohaku@slideshare.net(kato_kohaku) Genetic algorithm full scratch with R kato_kohaku 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 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/geneticalgorithmfullscratchwithr-180826104320-thumbnail.jpg?width=120&height=120&fit=bounds" /> 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

Genetic algorithm full scratch with R from Satoshi Kato

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0 Intoroduction & R implementation of "Interpretable predictions of　tree-based ensembles via actionable feature tweaking /slideshow/interpretable-predictions-oftreebasedensemblesviaactionablefeaturetweaking/86225925 interpretablepredictionsoftree-basedensemblesviaactionablefeaturetweaking-180116133613
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)]]>
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)]]> Tue, 16 Jan 2018 13:36:13 GMT /slideshow/interpretable-predictions-oftreebasedensemblesviaactionablefeaturetweaking/86225925 kato_kohaku@slideshare.net(kato_kohaku) Intoroduction & R implementation of "Interpretable predictions of　tree-based ensembles via actionable feature tweaking kato_kohaku 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) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/interpretablepredictionsoftree-basedensemblesviaactionablefeaturetweaking-180116133613-thumbnail.jpg?width=120&height=120&fit=bounds" /> 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)

Intoroduction & R implementation of "Interpretable predictions of tree-based ensembles via actionable feature tweaking from Satoshi Kato

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0 Multiple optimization and Non-dominated sorting with rPref package in R /slideshow/non-dominnt-sortandparetofrontwithrpref/75297886 non-dominntsortandparetofrontwithrpref-170422055152
introduction of Pareto optimal ,non-dominated sort and How-To-Use `rPref` package in R]]>
introduction of Pareto optimal ,non-dominated sort and How-To-Use `rPref` package in R]]> Sat, 22 Apr 2017 05:51:52 GMT /slideshow/non-dominnt-sortandparetofrontwithrpref/75297886 kato_kohaku@slideshare.net(kato_kohaku) Multiple optimization and Non-dominated sorting with rPref package in R kato_kohaku introduction of Pareto optimal ,non-dominated sort and How-To-Use `rPref` package in R <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/non-dominntsortandparetofrontwithrpref-170422055152-thumbnail.jpg?width=120&height=120&fit=bounds" /> introduction of Pareto optimal ,non-dominated sort and How-To-Use `rPref` package in R

Multiple optimization and Non-dominated sorting with rPref package in R from Satoshi Kato

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0 Deep forest (preliminary ver.) /slideshow/deep-forest-preliminary-ver/73177790 deepforesttemp-170315151444
暂定版なのでのちほど差し替えます闭闭>
暂定版なのでのちほど差し替えます闭闭> Wed, 15 Mar 2017 15:14:43 GMT /slideshow/deep-forest-preliminary-ver/73177790 kato_kohaku@slideshare.net(kato_kohaku) Deep forest (preliminary ver.) kato_kohaku 暂定版なのでのちほど差し替えます <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/deepforesttemp-170315151444-thumbnail.jpg?width=120&height=120&fit=bounds" /> 暂定版なのでのちほど差し替えます

Deep forest (preliminary ver.) from Satoshi Kato

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0 Introduction of "the alternate features search" using R /slideshow/introduction-alternate-featuresinlassor-71186764/71186764 introductionalternatefeaturesinlassor-170119142500
Introduction of the alternate features search using R, proposed in the paper. S. Hara, T. Maehara, Finding Alternate Features in Lasso, 1611.05940, 2016.]]>
Introduction of the alternate features search using R, proposed in the paper. S. Hara, T. Maehara, Finding Alternate Features in Lasso, 1611.05940, 2016.]]> Thu, 19 Jan 2017 14:24:59 GMT /slideshow/introduction-alternate-featuresinlassor-71186764/71186764 kato_kohaku@slideshare.net(kato_kohaku) Introduction of "the alternate features search" using R kato_kohaku Introduction of the alternate features search using R, proposed in the paper. S. Hara, T. Maehara, Finding Alternate Features in Lasso, 1611.05940, 2016. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/introductionalternatefeaturesinlassor-170119142500-thumbnail.jpg?width=120&height=120&fit=bounds" /> Introduction of the alternate features search using R, proposed in the paper. S. Hara, T. Maehara, Finding Alternate Features in Lasso, 1611.05940, 2016.

Introduction of "the alternate features search" using R from Satoshi Kato

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0 蹿辞谤别蝉迟贵濒辞辞谤パッケージを使った谤补苍诲辞尘贵辞谤别蝉迟の感度分析 /slideshow/sensitivity-analysis-usingforestfloor/64528616 sensitivityanalysisusingforestfloor-160730022428
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]]> Sat, 30 Jul 2016 02:24:28 GMT /slideshow/sensitivity-analysis-usingforestfloor/64528616 kato_kohaku@slideshare.net(kato_kohaku) 蹿辞谤别蝉迟贵濒辞辞谤パッケージを使った谤补苍诲辞尘贵辞谤别蝉迟の感度分析 kato_kohaku Introduction of sensitivity analysis for randamforest regression, binary classification and multi-class classification of random forest using {forestFloor} package <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/sensitivityanalysisusingforestfloor-160730022428-thumbnail.jpg?width=120&height=120&fit=bounds" /> Introduction of sensitivity analysis for randamforest regression, binary classification and multi-class classification of random forest using {forestFloor} package

蹿辞谤别蝉迟贵濒辞辞谤パッケージを使った谤补苍诲辞尘贵辞谤别蝉迟の感度分析 from Satoshi Kato

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0 Oracle property and_hdm_pkg_rigorouslasso /slideshow/oracle-property-andhdmpkgrigorouslasso/63213162 oraclepropertyandhdmpkgrigorouslasso-160619012516
Lasso,　R package, rigorous Lasso, Oracle property]]>
Lasso,　R package, rigorous Lasso, Oracle property]]> Sun, 19 Jun 2016 01:25:16 GMT /slideshow/oracle-property-andhdmpkgrigorouslasso/63213162 kato_kohaku@slideshare.net(kato_kohaku) Oracle property and_hdm_pkg_rigorouslasso kato_kohaku Lasso,　R package, rigorous Lasso, Oracle property <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/oraclepropertyandhdmpkgrigorouslasso-160619012516-thumbnail.jpg?width=120&height=120&fit=bounds" /> Lasso,　R package, rigorous Lasso, Oracle property

Oracle property and_hdm_pkg_rigorouslasso from Satoshi Kato

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0 Imputation of Missing Values using Random Forest /slideshow/imputation-of-missing-values-using-random-forest/61497703 imputationusingrandomforest-160429102301
missForest packageの紹介 “MissForest - nonparametric missing value imputation for mixed-type data (DJ Stekhoven, P Bühlmann (2011), Bioinformatics 28 (1), 112-118) ]]>
missForest packageの紹介 “MissForest - nonparametric missing value imputation for mixed-type data (DJ Stekhoven, P Bühlmann (2011), Bioinformatics 28 (1), 112-118) ]]> Fri, 29 Apr 2016 10:23:01 GMT /slideshow/imputation-of-missing-values-using-random-forest/61497703 kato_kohaku@slideshare.net(kato_kohaku) Imputation of Missing Values using Random Forest kato_kohaku missForest packageの紹介 “MissForest - nonparametric missing value imputation for mixed-type data (DJ Stekhoven, P Bühlmann (2011), Bioinformatics 28 (1), 112-118) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/imputationusingrandomforest-160429102301-thumbnail.jpg?width=120&height=120&fit=bounds" /> missForest packageの紹介 “MissForest - nonparametric missing value imputation for mixed-type data (DJ Stekhoven, P Bühlmann (2011), Bioinformatics 28 (1), 112-118)

Imputation of Missing Values using Random Forest from Satoshi Kato

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0 Interpreting Tree Ensembles with inTrees /slideshow/interpreting-tree-ensembles-with-intrees/61490574 intreepkgrandomforest-160429061823
inTrees R Package random forest]]>
inTrees R Package random forest]]> Fri, 29 Apr 2016 06:18:23 GMT /slideshow/interpreting-tree-ensembles-with-intrees/61490574 kato_kohaku@slideshare.net(kato_kohaku) Interpreting Tree Ensembles with inTrees kato_kohaku inTrees R Package random forest <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/intreepkgrandomforest-160429061823-thumbnail.jpg?width=120&height=120&fit=bounds" /> inTrees R Package random forest

Interpreting Tree Ensembles with inTrees from Satoshi Kato

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0 https://public.slidesharecdn.com/v2/images/profile-picture.png https://cdn.slidesharecdn.com/ss_thumbnails/powerpointwithofficer-200404014557-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/how-to-generate-powerpoint-slides-nonmanually-using-r/231387408 How to generate PowerP... https://cdn.slidesharecdn.com/ss_thumbnails/dimensionalityreductionwithtsneumapusingr-190927154000-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/dimensionality-reduction-with-tsne-and-umap-using-r-176806642/176806642 Dimensionality reducti... https://cdn.slidesharecdn.com/ss_thumbnails/exploratorydataanalysisusingxgboost-190516135022-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/exploratory-data-analysis-using-xgboost-package-in-r-146048320/146048320 Exploratory data analy...