Banten: Food Prices in Banten

CRAN

ifpd: Indonesia Food Prices Data

R: Food Prices in Banten
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function processMathHTML

heaviness: Heaviness from parent packages

CRAN

pkgndep: Analyze Dependency Heaviness of R Packages

R: Heaviness from parent packages
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function

Bagging: Bagging

GITHUB

msats5/capstoneProject:

R: Bagging
BaggingR Documentation
Bagging

bagging: Bagging

GITHUB

pkuhnert/diet: Performs an analysis of diet data using univariate trees

R: Bagging
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function processMathHTML() {

WA: Weighted averaging (WA) regression and calibration

CRAN

rioja: Analysis of Quaternary Science Data

R: Weighted averaging (WA) regression and calibration
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt

WA: Weighted averaging (WA) regression and calibration

GITHUB

nsj3/rioja: Analysis of Quaternary Science Data

R: Weighted averaging (WA) regression and calibration
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt

bagging: bagging method

GITHUB

fhpinto/autoBagging: Learning to Rank Bagging Workflows with Metalearning

R: bagging method
baggingR Documentation
bagging method

bagging: Bagging data

CRAN

eat: Efficiency Analysis Trees

R: Bagging data
baggingR Documentation
Bagging data

bagging: Applies the Bagging algorithm to a dataset

GITHUB

Fuzzy-Logix/AdapteR: Converts R syntax to SQL to provide fast analytics using in-database C++ library DB Lytix.

R: Applies the Bagging algorithm to a dataset
baggingR Documentation
Applies the Bagging algorithm to a dataset

bagging: bagging method

CRAN

autoBagging: Learning to Rank Bagging Workflows with Metalearning

R: bagging method
baggingR Documentation
bagging method

bagging: Bagging data

GITHUB

MiriamEsteve/EAT: Efficiency Analysis Trees

R: Bagging data
baggingR Documentation
Bagging data

heavy: Robust Estimation Using Heavy-Tailed Distributions

CRAN

heavy: Robust Estimation Using Heavy-Tailed Distributions

Package: heavy
Version: 0.38.196
Title: Robust Estimation Using Heavy-Tailed Distributions

bag: A General Framework For Bagging

CRAN

caret: Classification and Regression Training

R: A General Framework For Bagging
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function

bag: Calculates the bag

GITHUB

jkruppa/gemPlot: Calculation and visualization of gemplots (3-dimensional extension of boxplot and bagplot).

R: Calculates the bag
bagR Documentation
Calculates the bag

bag: Calculates the bag

CRAN

RepeatedHighDim: Methods for High-Dimensional Repeated Measures Data

R: Calculates the bag
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function processMathHTML

bag: Bagging Discrete-Time Survival Trees

CRAN

DStree: Recursive Partitioning for Discrete-Time Survival Trees

R: Bagging Discrete-Time Survival Trees
bagR Documentation
Bagging Discrete-Time Survival Trees

bag: Multi-indicators / "Bag o Words"

GITHUB

nfultz/stackoverflow: Stack Overflow's Greatest Hits

R: Multi-indicators / "Bag o Words"
bagR Documentation
Multi-indicators / "Bag o Words"

bagging: Ensemble bagging classifier for multinomial classification

CRAN

bagRboostR: Ensemble bagging and boosting classifiers

R: Ensemble bagging classifier for multinomial classification
baggingR Documentation
Ensemble bagging classifier

vendor: vendor

GITHUB

bcBusinessStats/data1135: Data for Business Statistics OPER1135

R: vendor
vendorR Documentation
vendor

BAGGING: Classification using Bagging

CRAN

fdm2id: Data Mining and R Programming for Beginners

R: Classification using Bagging
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function