{"Package":"rtemis","Version":"0.79","Title":"Machine Learning and Visualization","Date":"2019-07-02","Authors@R":"person(given = \"Efstathios D.\", family = \"Gennatas\", role = c(\"aut\", \"cre\"), email = \"gennatas@gmail.com\", comment = c(ORCID = \"0000-0001-9280-3609\"))","Maintainer":"Efstathios D. Gennatas ","Description":"Advanced Machine Learning and Visualization made efficient and accessible. Unsupervised Learning (Clustering, Decomposition), Supervised Learning (Classification, Regression, Survival Analysis), Cross-Decomposition, Bagging, Boosting, Meta-models. Static and dynamic graphs.","License":"GPL (>=3)","URL":"https://rtemis.netlify.com","ByteCompile":"yes","Imports":"grDevices, graphics, stats, methods, utils, parallel, R6, data.table, crayon, future, magrittr","Suggests":"ada, ANTsR, arm, bartMachine, base64enc, cluster, C50, data.tree, deepnet, dendextend (>= 0.18.0), doParallel, d3heatmap, earth, EMCluster, extraTrees, evtree, e1071, fansi, fastICA, flexclust, FNN, foreach, fpc, gamsel, gbm, gbm3, ggplot2, glmnet, GPArotation, grid, gsubfn, heatmaply, hopach, htmlwidgets, h2o, ica, imager, inTrees, iRF, keras, kernlab, knitr, lars, lavaan, leaps, lle, matrixStats, MASS, mda, mgcv, mlbench, missForest, mxnet, nlme, nnet, NMF, np, nsprcomp, oro.nifti, partykit, pbapply, plotly, polspline, PPtree, pROC, psych, PMA, png, plotrix, plyr, pvclust, qrnn, randomForest, randomForestSRC, ranger, rCUR, RColorBrewer, RNifti, ROCR, rpart, rpart.plot, rstudioapi, Rtsne, R.utils, scales (>= 0.2.5), sgd, snow, snowfall, sparklyr, splines2, spls, survival, tgp, vegan, xgboost, rmarkdown, uwot","Remotes":"ANTsX/ANTsR, gbm-developers/gbm3, airoldilab/sgd, jlmelville/uwot","RoxygenNote":"6.1.1","VignetteBuilder":"knitr","repoType":"github","tarballUrl":"https://api.github.com/repos/egenn/rtemis/tarball/v0.79","jsonAuthors":[{"name":"Efstathios D. Gennatas","email":"gennatas@gmail.com","maintainer":true}],"readme":"**_rtemis_** Machine Learning and Visualization [![Build Status](https://travis-ci.com/egenn/rtemis.svg?branch=master)](https://travis-ci.com/egenn/rtemis)\n===============================================\nA platform for advanced Machine Learning research and applications. \nThe goal of rtemis is to make data science efficient and accessible with no compromise on flexibility.\n\n

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\n\n[__Online Documentation and vignettes__](https://rtemis.netlify.com)\n\n### Installation\nSee [here](https://rtemis.netlify.com/setup.html) for more setup and installation instructions.\n\n```r\ninstall.packages(\"remotes\")\nremotes::install_github(\"egenn/rtemis\")\n```\n\n### 10-second intro to __rtemis__\nInstall dependencies if they are not already installed:\n```r\npackages <- c(\"pbapply\", \"ranger\")\n.add <- !packages %in% installed.packages()\ninstall.packages(packages[.add])\n```\n\nLoad rtemis and get cross-validated random forest performance on the iris dataset:\n```r\nlibrary(rtemis)\nmod <- elevate(iris)\nmod$plot()\n```\n\n### What's new\n* __v. 0.78__: First public release, April 2019\n\n### Features\n* __Visualization__\n - Static: **_mplot3_** family (base graphics)\n - Dynamic: **_dplot3_** family ([plotly](https://plot.ly/r/))\n* __Unsupervised Learning__\n - Clustering: **_u.\\*_**\n - Decomposition: **_d.\\*_**\n* __Supervised Learning__\n - Classification, Regression, Survival Analysis: **_s.\\*_**\n* __Cross-Decomposition__\n - Sparse Canonical Correlation / Sparse Decomposition: **_x.\\*_**\n* __Meta-Models__ \n [Have been temporarily removed for updating]\n - Model Stacking: **_metaMod()_**\n - Modality Stacking: **_metaFeat()_**\n - Group-weighted Stacking: **_metaGroup()_**\n\n### Ongoing work\n* Novel algorithms developed in __rtemis__ will generally be added to this public repository as soon as the corresponding papers or preprints are published.\n* R Documentation is ongoing and should be completed soon.\n* __rtemis__ is under active development with many enhancements and extensions in the works\n---\n

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\n\n2019 Efstathios D. Gennatas ","jobInfo":{"package":"rtemis","version":"v0.79","parsingStatus":"success","parserVersion":1,"parsedAt":"2021-05-21T19:30:13+0000"}}

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