Man pages for jsalminen/KaggleSolveR

addFactorLevelAdd a new level to a factor
cleanDataClean training and test data sets
countNAsCount the number of NAs in each column of a data frame
createConfigFileCreate configuration file for a data set
createDateFeaturesCreate new features based on date fields
fitFinalModelFit all training data using the best model with optimized...
fixDataRepresentationChange the data representation depending to fit requirements...
fix_factor_levelsSynchronize factor levels between train and test sets
getEvaluationPredict and evaluate performance of a machine learning model
getModelGet an optimized machine learning model
getModelListGet a list of models to fit
getModelMatrixConvert a data frame to a model matrix
getNumClassFind the number of different classes in labels.
getPartitionIndexGet partition index for training and validation sets
getPreProcFactorPreprocess all factor columns of a data frame
getPreProcNumericPreprocess all numeric columns of a data frame
getSingleValueColsFind data frame columns where all values are the same
getSparseMatrixConvert a data frame to a sparse model matrix
getSubmissionCreate submission data frame
getTaskParamsGet task specific parameters
identifyTaskIdentify the type of the learning task
imputeDefaultImpute missing values with default values
imputeNAImpute missing values in a column or vector
imputeNAsImpute missing values in train or test data set
imputeValueReplace NAs with a specific value
isBetterCheck if the new score is better than the current best score
processTextPreprocess all character columns of a data frame
selectModelSelect the best performing model
splitDataSplit data to training and validation sets
updateBestModelUpdate best_fit_model if the new model is better than the...
update_classesChange classes in a data frame according to configuration...
jsalminen/KaggleSolveR documentation built on May 20, 2019, 5:43 p.m.