Package: qeML 1.2
qeML: Quick and Easy Machine Learning Tools
The letters 'qe' in the package title stand for "quick and easy," alluding to the convenience goal of the package. We bring together a variety of machine learning (ML) tools from standard R packages, providing wrappers with a simple, convenient, and uniform interface.
Authors:
qeML_1.2.tar.gz
qeML_1.2.zip(r-4.5)qeML_1.2.zip(r-4.4)qeML_1.2.zip(r-4.3)
qeML_1.2.tgz(r-4.4-any)qeML_1.2.tgz(r-4.3-any)
qeML_1.2.tar.gz(r-4.5-noble)qeML_1.2.tar.gz(r-4.4-noble)
qeML_1.2.tgz(r-4.4-emscripten)qeML_1.2.tgz(r-4.3-emscripten)
qeML.pdf |qeML.html✨
qeML/json (API)
| # Install 'qeML' in R: |
| install.packages('qeML', repos = c('https://matloff.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/matloff/qeml/issues
- CancerMenopause - Swedish breast cancer.
- EPIWgProduct - EPI Growth Data
- ThyroidDisease - Thyroid Disease
- courseRecords - Records from several offerings of a certain course.
- currency - Pre-Euro Era Currency Fluctuations
- day - Bike sharing data.
- day1 - Bike sharing data.
- day2 - Bike sharing data.
- empAttrition - Employee Attrition Data
- english - English vocabulary data
- forest500 - Subset of the Covertype data.
- iranChurn - Iranian Customer Churn Data
- lsa - Law School Admissions Data
- ltrfreqs - Letter Frequencies
- mlb - Major Leage Baseball player data set.
- mlb1 - Major Leage Baseball player data set.
- mlens - MovieLens User Summary Data
- nyctaxi - New York City Taxi Data
- oliveoils - Italian olive oils data set.
- prgeng - Silicon Valley programmers and engineers data
- quizDocs - Course quiz documents
- quizzes - Course quiz documents
- svcensus - Silicon Valley programmers and engineers data
- weatherTS - Weather Time Series
Last updated 12 hours agofrom:c654046d41. Checks:OK: 1 WARNING: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 06 2024 |
| R-4.5-win | WARNING | Nov 06 2024 |
| R-4.5-linux | WARNING | Nov 06 2024 |
| R-4.4-win | WARNING | Nov 06 2024 |
| R-4.4-mac | WARNING | Nov 06 2024 |
| R-4.3-win | WARNING | Nov 06 2024 |
| R-4.3-mac | WARNING | Nov 06 2024 |
Exports:buildQEcallcartesianFactorcheckPkgLoadedDatadataToTopLevelsdoubleDevalrfactorToTopLevelslevelCountsnewDFRowplotClassesUMAPplotPairedResidsqeAdaBoostqeCompareqeDeepnetqeDTqeFOCIqeFOCImultqeFOCIrandqeFreqParcoordqeFTqeGBoostqeKNNqeKNNMVqeLASSOqeLeaveOut1VarqeLightGBoostqeLinqeLinKNNqeLinMVqeLogitqeLogitMVqeMittalGraphqeNCVregCVqeNeuralqeNeuralTorchqeParallelqePCAqePlotCurvesqePolyLASSOqePolyLinqePolyLinKNNqePolyLogqeRareLevelsqeRFqeRFgrfqeRFrangerqeROCqeRpartqeSVMqeTextqeTSqeUMAPqeXGBoostreplicMeansMatrix
Dependencies:abindbackportsbase64encBHbootbroombslibcachemcarcarDataclicodetoolscolorspacecowplotcpp11data.tableDerivDiceKrigingdigestdoBydplyrevaluatefansifarverfastmapfloatFNNFOCIfontawesomeforeachFormulafsgbmgenericsggplot2glmnetgluegmpgrfgtablegtoolshighrhtmltoolsisobanditeratorsjquerylibjsonliteknitrlabelinglatticelgrlifecyclelme4lmtestmagrittrMASSMatrixMatrixExtraMatrixModelsmemoisemgcvmicrobenchmarkmimeminqamlapimodelrmunsellmvtnormnlmenloptrNLPnnetnumDerivpartoolspbkrtestpdistpillarpkgconfigpolyregproxypurrrquantregR.methodsS3R.ooR.utilsR6RANNrappdirsRColorBrewerRcppRcppArmadilloRcppEigenregtoolsRhpcBLASctlrjerlangrmarkdownrpartrpart.plotrsparsesandwichsassscalesshapeslamSparseMstringistringrsurvivaltext2vectibbletidyrtidyselecttinytextmtoweranNAtufteutf8vctrsviridisLitewithrxfunxml2yamlzoo
Feature_Selection
Rendered fromFeature_Selection.Rmdusingknitr::rmarkdownon Nov 06 2024.Last update: 2023-09-19
Started: 2023-02-22
Function List
Rendered fromFunction_List.Rmdusingknitr::rmarkdownon Nov 06 2024.Last update: 2023-09-19
Started: 2023-08-16
Machine Learning Overview
Rendered fromML_Overview.Rmdusingknitr::rmarkdownon Nov 06 2024.Last update: 2023-09-20
Started: 2023-02-22
Problems with P-values
Rendered fromNoPValues.Rmdusingknitr::rmarkdownon Nov 06 2024.Last update: 2023-09-27
Started: 2023-09-02
Overfitting
Rendered fromOverfitting.Rmdusingknitr::rmarkdownon Nov 06 2024.Last update: 2023-09-19
Started: 2023-02-22
PCA and UMAP
Rendered fromPCA_and_UMAP.Rmdusingknitr::rmarkdownon Nov 06 2024.Last update: 2023-09-19
Started: 2023-02-22
Quick Start
Rendered fromQuick_Start.Rmdusingknitr::rmarkdownon Nov 06 2024.Last update: 2023-09-19
Started: 2023-02-22
Unbalanced Classes
Rendered fromUnbalanced_Classes.Rmdusingknitr::rmarkdownon Nov 06 2024.Last update: 2023-09-20
Started: 2023-02-22
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Advanced Plots | plotClassesUMAP plotPairedResids qeFreqParcoord qeMittalGraph qePlotCurves |
| Swedish breast cancer. | CancerMenopause |
| Records from several offerings of a certain course. | courseRecords |
| Pre-Euro Era Currency Fluctuations | currency |
| Bike sharing data. | day day1 day2 |
| Double Descent Phenomenon | doubleD plot.doubleD |
| Employee Attrition Data | empAttrition |
| English vocabulary data | english |
| EPI Growth Data | EPIWgProduct |
| Feature Selection and Model Building | predict.qeText predict.qeTS qeCompare qeFT qeText qeTS |
| Subset of the Covertype data. | forest500 |
| Iranian Customer Churn Data | iranChurn |
| Law School Admissions Data | lsa |
| Letter Frequencies | ltrfreqs |
| Major Leage Baseball player data set. | mlb mlb1 |
| MovieLens User Summary Data | mlens |
| UCI adult income data set, adapted | newAdult newadult |
| New York City Taxi Data | nyctaxi |
| Italian olive oils data set. | oliveoils |
| Prediction with Missing Values | predict.qeKNNMV predict.qeLinMV predict.qeLogitMV qeKNNMV qeLinMV qeLogitMV |
| Silicon Valley programmers and engineers data | pef prgeng svcensus |
| Quick-and-Easy Machine Learning Wrappers | checkPkgLoaded plot.qeLASSO plot.qePoly plot.qeRF plot.qeRpart predict.qeAdaBoost predict.qeDeepnet predict.qeGBoost predict.qeIso predict.qeKNN predict.qeLASSO predict.qeLightGBoost predict.qeLin predict.qeLogit predict.qeNCVregCV predict.qeNeural predict.qeParallel predict.qePCA predict.qePoly predict.qePolyLin predict.qePolyLinKNN predict.qePolyLog predict.qeRF predict.qeRFgrf predict.qeRFranger predict.qeRpart predict.qeSVM predict.qeUMAP qeAdaBoost qeDeepnet qeDT qeFOCI qeFOCImult qeFOCIrand qeGBoost qeIso qeKNN qeLASSO qeLightGBoost qeLin qeLinKNN qeLogit qeNCVregCV qeNeural qeParallel qePCA qePoly qePolyLASSO qePolyLin qePolyLinKNN qePolyLog qeRF qeRFgrf qeRFranger qeROC qeRpart qeSVM qeUMAP qeXGBoost |
| Course quiz documents | quizDocs quizzes |
| R Factor Utilities | cartesianFactor dataToTopLevels factorToTopLevels levelCounts qeRareLevels |
| Thyroid Disease | ThyroidDisease |
| Utilities | buildQEcall evalr newDFRow |
| Utilities | buildQEcall Data evalr newDFRow replicMeansMatrix |
| Variable Importance Measures | qeLeaveOut1Var |
| Weather Time Series | weatherTS |
