Files in ssi-ashraf/superml
Build Machine Learning Models Like Using Python's Scikit-Learn Library in R

CODE_OF_CONDUCT.md

DESCRIPTION

LICENSE

NAMESPACE

NEWS.md R/CountVectorizer.R R/GridSearch.R R/KMeansTrainer.R R/KNNTrainer.R R/LMTrainer.R R/LabelEncoder.R R/NBTrainer.R R/RandomForest.R R/RandomSearch.R R/SVMTrainer.R R/TfidfVectorizer.R R/XGBoost.R R/bm25.R R/data.R R/super_utils.R R/target_encoders.R README.Rmd README.md

_pkgdown.yml

appveyor.yml

cran-comments.md

data-raw/cla_test.csv

data-raw/cla_train.csv

data-raw/process_data.R

data-raw/reg_test.csv

data-raw/reg_train.csv

data/cla_train.rda

data/reg_train.rda

man/CountVectorizer.Rd man/Counter.Rd man/GridSearchCV.Rd man/KMeansTrainer.Rd man/KNNTrainer.Rd man/LMTrainer.Rd man/LabelEncoder.Rd man/NBTrainer.Rd man/RFTrainer.Rd man/RandomSearchCV.Rd man/SVMTrainer.Rd man/TfIdfVectorizer.Rd man/XGBTrainer.Rd man/bm25.Rd man/check_package.Rd man/cla_train.Rd man/kFoldMean.Rd man/reg_train.Rd man/smoothMean.Rd man/testdata.Rd

superml.Rproj

superml_0.4.0.tar.gz

tests/testthat.R vignettes/introduction.Rmd

ssi-ashraf/superml documentation built on Nov. 5, 2019, 9:18 a.m.

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