DBItest (>= 1.7.0), gert, gh, knitr, rmarkdown, rvest,
testthat, xml2

DBItest (>= 1.7.0), gert, gh, knitr, rmarkdown, hms, rvest,
testthat, xml2

'RcppExports.R' 'SQLiteConnection.R' 'SQLiteDriver.R'
'SQLiteResult.R' 'coerce.R' 'connect.R' 'copy.R' 'datasetsDb.R'
'deprecated.R' 'export.R' 'extensions.R' 'names.R'
'pkgconfig.R' 'query.R' 'regularExpressions.R' 'rownames.R'
'rstudioConnections.R' 'table.R' 'transactions.R' 'utils.R'
'zzz.R'

Embeds the SQLite database engine in R and
provides an interface compliant with the DBI package. The source for
the SQLite engine is included.

Math and String Extension Functions for RSQLite
This package uses SQLite's loadable extension feature to
provide a number of additional SQL functions and aggregates.
The package is a wrapper of extension functions written by Liam
Healy and made available through the SQLite website
(http://www.sqlite.org/contrib).  Math: acos, asin, atan, atn2,
atan2, acosh, asinh, atanh, difference, degrees, radians, cos,
sin, tan, cot, cosh, sinh, tanh, coth, exp, log, log10, power,
sign, sqrt, square, ceil, floor, pi. String: replicate,
charindex, leftstr, rightstr, ltrim, rtrim, trim, replace,
reverse, proper, padl, padr, padc, strfilter. Aggregate: stdev,
variance, mode, median, lower_quartile, upper_quartile.

Implementations of Semi-Supervised Learning Approaches for
Classification
c(person("Jesse", "Krijthe", role = c("aut", "cre"),
email = "jkrijthe@gmail.com"))
methods, Rcpp, MASS, kernlab, quadprog, Matrix, dplyr, tidyr,
ggplot2, reshape2, scales, cluster
testthat, rmarkdown, SparseM, numDeriv, LiblineaR
A collection of implementations of semi-supervised classifiers and methods to evaluate their performance. The package includes implementations of, among others, Implicitly Constrained Learning, Moment Constrained Learning, the Transductive SVM, Manifold regularization, Maximum Contrastive Pessimistic Likelihood estimation, S4VM and WellSVM.
'Generics.R' 'Classifier.R' 'CrossValidation.R'
'LeastSquaresClassifier.R' 'EMLeastSquaresClassifier.R'
'NormalBasedClassifier.R' 'LinearDiscriminantClassifier.R'
'EMLinearDiscriminantClassifier.R' 'NearestMeanClassifier.R'
'EMNearestMeanClassifier.R' 'LogisticRegression.R'
'EntropyRegularizedLogisticRegression.R' 'Evaluate.R'
'GRFClassifier.R' 'GenerateSSLData.R' 'HelperFunctions.R'
'ICLeastSquaresClassifier.R' 'ICLinearDiscriminantClassifier.R'
'KernelLeastSquaresClassifier.R'
'KernelICLeastSquaresClassifier.R'
'LaplacianKernelLeastSquaresClassifier.R' 'LaplacianSVM.R'
'LearningCurve.R' 'LinearSVM.R' 'LogisticLossClassifier.R'
'MCLinearDiscriminantClassifier.R' 'MCNearestMeanClassifier.R'
'MCPLDA.R' 'MajorityClassClassifier.R' 'Measures.R'
'Plotting.R' 'QuadraticDiscriminantClassifier.R' 'RSSL.R'
'RcppExports.R' 'S4VM.R' 'SVM.R' 'SelfLearning.R' 'TSVM.R'
'USMLeastSquaresClassifier.R' 'WellSVM.R' 'scaleMatrix.R'
'svmd.R' 'svmlin.R' 'testdata-data.R'