regtools-package: Overview and Package Reference Guide

In matloff/regtools: Regression and Classification Tools

Overview and Package Reference Guide

Description

This package provides a broad collection of functions useful for regression and classification analysis, and machine learning.

Function List

Parametric modeling:

• nonlinear regression: nlshc

• ridge regression: ridgelm, plot

• missing values (also see our toweranNA package): lmac,makeNA,coef.lmac,vcov.lmac,pcac

Diagnostic plots:

• regression diagnostics: parvsnonparplot, nonparvsxplot, nonparvarplot

• other: boundaryplot, nonparvsxplot

Classification:

• unbalanced data: classadjust (see UnbalancedClasses.md)

• All vs. All: avalogtrn, avalogpred

• k-NN reweighting: exploreExpVars, plotExpVars, knnFineTune

Machine learning (also see qeML package):

• k-NN: kNN, kmin, knnest, knntrn, preprocessx, meany, vary, loclin, predict, kmin, pwplot, bestKperPoint, knnFineTune

• neural networks: krsFit,multCol

• advanced grid search: fineTuning, fineTuningPar, plot.tuner, knnFineTune

• loss: l1, l2, MAPE, ROC

Dummies and R factors Utilities:

• conversion between factors and dummies: dummiesToFactor, dummiesToInt, factorsToDummies, factorToDummies, factorTo012etc, dummiesToInt, hasFactors, charsToFactors, makeAllNumeric

• dealing with superset and subsets of factors: toSuperFactor, toSubFactor

Statistics:

• mm

Matrix:

• multCols, constCols

Time series:

• convert rectangular to TS: TStoX

Text processing:

• textToXY

Misc.:

• scaling: mmscale, unscale

• data frames: catDFRow, tabletofakedf

• R: getNamedArgs, ulist

• discretize

matloff/regtools documentation built on July 17, 2022, 10:10 a.m.