Machine Learning Using R
DOI10.1007/978-1-4842-4215-5zbMath1423.68007OpenAlexW2562262019MaRDI QIDQ5233756
Karthik Ramasubramanian, Abhishek Singh
Publication date: 6 September 2019
Full work available at URL: https://doi.org/10.1007/978-1-4842-4215-5
samplingregression analysistime serieshypothesis testingresamplingsupervised learningtext miningcross-validationscalabilityartificial neural networkscluster analysisreinforcement learningdata miningfuzzy clusteringrecurrent neural networksunsupervised learningdecision treessupport vector machinessummary statisticsmachine learningfeature selectiondata sciencebias-variance trade-offstatistical learningpopulation variancemodel evaluationsampling biassemi-supervised learningexploratory analysiscorrelation analysisconvolutional neural networksdeep learningpopulation meansampling errordata visualisationKerasrule miningensemble techniqueshyper-parameter optimisationmodel performance improvementnaïve Bayes methodTensorFlow
Introductory exposition (textbooks, tutorial papers, etc.) pertaining to computer science (68-01) Learning and adaptive systems in artificial intelligence (68T05) Research exposition (monographs, survey articles) pertaining to computer science (68-02)
Uses Software
- R
- forecast
- tseries
- ROCR
- ggplot2
- tm
- wordcloud
- arules
- nnet
- Kernlab
- e1071
- ipred
- caret
- mlbench
- rJava
- Hadoop
- clValid
- corrplot
- randomForest
- reshape2
- astsa
- FinTS
- stringr
- C4.5
- doParallel
- caTools
- dplyr
- Rugarch
- GPfit
- ggmap
- NeuralNetTools
- TensorFlow
- mscstexta4r
- Keras
- googleVis
- dbscan
- h2o
- lubridate
- rBayesianOptimization
- NLP
- data.table
- rhdfs
- rmr2
- SparkR
- MLmetrics
- plotROC
- gmodels
- waterfall
- ggrepel
- CHAID
- splitstackshape
- recommenderlab
- LSAfun
- openNLP
- SnowballC
- aTSA
- caretEnsemble
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