R package citation, R package reverse dependencies, R package scholars, install an r package from GitHub hy is package acceptance pending why is package undeliverable amazon why is package on hold dhl tour packages why in r package r and r package full form why is r free why r is bad which r package to install which r package has which r package which r package version which r package readxl which r package ggplot which r package fread which r package license where is package.json where is package-lock.json where is package.swift where is package explorer in eclipse where is package where is package manager unity where is package installer android where is package manager console in visual studio who r package which r package to install which r package version who is package who is package deal who is package design r and r package full form r and r package meaning what r package has what package r what is package in java what is package what is package-lock.json what is package in python what is package.json what is package installer do r package can't install r packages r can't find package r can't load package can't load xlsx package r can't install psych package r can't install sf package r Write if else in NONMEM pk pd
D2MCS
View on CRAN: Click
here
Download and install D2MCS package within the R console
Install from CRAN:
install.packages("D2MCS")
Install from Github:
library("remotes")
install_github("cran/D2MCS")
Install by package version:
library("remotes")
install_version("D2MCS", "1.0.1")
Attach the package and use:
library("D2MCS")
Maintained by
Miguel Ferreiro-Díaz
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-05-07
Latest Update: 2022-08-23
Description:
Provides a novel framework to able to automatically develop and deploy
an accurate Multiple Classifier System based on the feature-clustering
distribution achieved from an input dataset. 'D2MCS' was developed focused on
four main aspects: (i) the ability to determine an effective method to
evaluate the independence of features, (ii) the identification of the
optimal number of feature clusters, (iii) the training and tuning of ML
models and (iv) the execution of voting schemes to combine the outputs of
each classifier comprising the Multiple Classifier System.
How to cite:
Miguel Ferreiro-Díaz (2021). D2MCS: Data Driving Multiple Classifier System. R package version 1.0.1, https://cran.r-project.org/web/packages/D2MCS. Accessed 22 Dec. 2024.
Previous versions and publish date:
1.0.0 (2021-05-07 11:30)
Other packages that cited D2MCS R package
View D2MCS citation profile
Other R packages that D2MCS depends,
imports, suggests or enhances
Complete documentation for D2MCS
Functions, R codes and Examples using
the D2MCS R package
Some associated functions: Accuracy . BinaryPlot . ChiSquareHeuristic . ClassMajorityVoting . ClassWeightedVoting . ClassificationOutput . ClusterPredictions . CombinedMetrics . CombinedVoting . ConfMatrix . D2MCS . DIterator . Dataset . DatasetLoader . DefaultModelFit . DependencyBasedStrategy . DependencyBasedStrategyConfiguration . ExecutedModels . FIterator . FN . FP . FinalPred . FisherTestHeuristic . GainRatioHeuristic . GenericClusteringStrategy . GenericHeuristic . GenericModelFit . GenericPlot . HDDataset . HDSubset . InformationGainHeuristic . Kappa . KendallHeuristic . MCC . MCCHeuristic . MeasureFunction . Methodology . MinimizeFN . MinimizeFP . Model . MultinformationHeuristic . NPV . NoProbability . OddsRatioHeuristic . PPV . PearsonHeuristic . Precision . Prediction . PredictionOutput . ProbAverageVoting . ProbAverageWeightedVoting . ProbBasedMethodology . Recall . Sensitivity . SimpleStrategy . SimpleVoting . SingleVoting . SpearmanHeuristic . Specificity . StrategyConfiguration . Subset . SummaryFunction . TN . TP . TrainFunction . TrainOutput . Trainset . TwoClass . TypeBasedStrategy . UseProbability . VotingStrategy .
Some associated R codes: D2MCS.R . clustering.heuristics.ChiSquareHeuristic.R . clustering.heuristics.FisherTestHeuristic.R . clustering.heuristics.GainRatioHeuristic.R . clustering.heuristics.GenericHeuristic.R . clustering.heuristics.InformationGainHeuristic.R . clustering.heuristics.KendallHeuristic.R . clustering.heuristics.MCCHeuristic.R . clustering.heuristics.MultinformationHeuristic.R . clustering.heuristics.OddsRatioHeuristic.R . clustering.heuristics.PearsonHeuristic.R . clustering.heuristics.SpearmanHeuristic.R . clustering.plot.BinaryPlot.R . clustering.plot.GenericPlot.R . clustering.strategies.DependencyBasedStrategy.R . clustering.strategies.DependencyBasedStrategyConfiguration.R . clustering.strategies.GenericClusteringStrategy.R . clustering.strategies.SimpleStrategy.R . clustering.strategies.StrategyConfiguration.R . clustering.strategies.TypeBasedStrategy.R . data.DIterator.R . data.Dataset.R . data.DatasetLoader.R . data.FIterator.R . data.HDDataset.R . data.HDSubset.R . data.Subset.R . data.Trainset.R . measures.Accuracy.R . measures.ConfMatrix.R . measures.FN.R . measures.FP.R . measures.Kappa.R . measures.MCC.R . measures.MeasureFunction.R . measures.NPV.R . measures.PPV.R . measures.Precision.R . measures.Recall.R . measures.Sensitivity.R . measures.Specificity.R . measures.TN.R . measures.TP.R . models.ExecutedModels.R . models.Model.R . models.summaryFunction.NoProbability.R . models.summaryFunction.SummaryFunction.R . models.summaryFunction.UseProbability.R . models.trainFunctions.TrainFunction.R . models.trainFunctions.TwoClass.R . models.utility.DefaultModelFit.R . models.utility.GenericModelFit.R . prediction.ClassMajorityVoting.R . prediction.ClassWeightedVoting.R . prediction.ClassificationOutput.R . prediction.ClusterPredictions.R . prediction.CombinedMetrics.R . prediction.CombinedVoting.R . prediction.FinalPred.R . prediction.Methodology.R . prediction.MinimizeFN.R . prediction.MinimizeFP.R . prediction.Prediction.R . prediction.PredictionOutput.R . prediction.ProbAverageVoting.R . prediction.ProbAverageWeightedVoting.R . prediction.ProbBasedMethodology.R . prediction.SimpleVoting.R . prediction.SingleVoting.R . prediction.TrainOutput.R . prediction.VotingStrategy.R . Full D2MCS package functions and examples
Downloads during the last 30 days
Get rewarded with contribution points by
helping add
Reviews / comments / questions /suggestions ↴↴↴
Today's Hot Picks in Authors and Packages
LOGANTree
Enables researchers to model log-file data from computer-based assessments using machine-learning te ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Qi Qin (view profile)
composits
A compositional multivariate and univariate time series outlier ensemble.It uses the four R packages ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Sevvandi Kandanaarachchi (view profile)
wordspace
An interactive laboratory for research on distributional semantic models ('DSM', see < ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Stephanie Evert (view profile)
tropAlgebra
It includes functions like tropical addition, tropical multiplication for vectors and matrices. In t ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Muhammad Kashif Hanif (view profile)
quickcode
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Obinna Obianom (view profile)
dmlalg
Implementation of double machine learning (DML) algorithms in R,
based on Emmenegger and Buehlmann ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Corinne Emmenegger (view profile)