Man pages for emil
Evaluation of Modeling without Information Leakage

as.modeling_procedureCoerce to modeling procedure
dichotomizeDichotomize time-to-event data
emilIntroduction to the emil package
error_funPerformance estimation functions
evaluateEvaluate a modeling procedure
extensionExtending the emil framework with user-defined methods
factor_to_logicalConvert factors to logicals
fillReplace values with something else
fitFit a model
fit_caretFit a model using the 'caret' package
fit_cforestFit conditional inference forest
fit_coxphFit Cox proportional hazards model
fit_glmnetFit elastic net, LASSO or ridge regression model
fit_ldaFit linear discriminant
fit_lmFit a linear model fitted with ordinary least squares
fit_naive_bayesFit a naive Bayes classifier
fit_pamrFit nearest shrunken centroids model.
fit_qdaFit quadratic discriminant.
fit_randomForestFit random forest.
fit_rpartFit a decision tree
fit_svmFit a support vector machine
get_colorGet color palettes
get_importanceFeature (variable) importance of a fitted model
get_performanceExtract prediction performance
get_predictionExtract predictions from modeling results
get_responseExtract the response from a data set
get_tuningExtract parameter tuning statistics
image.resampleVisualize resampling scheme
importance_glmnetFeature importance extractor for elastic net models
importance_pamrFeature importance of nearest shrunken centroids.
importance_randomForestFeature importance of random forest.
imputeRegular imputation
indentIncrease indentation
index_fitConvert a fold to row indexes of fittdng or test set
is_blankWrapper for several methods to test if a variable is empty
is_constantCheck if an object contains more than one unique value
is_multi_procedureDetect if modeling results contains multiple procedures
learning_curveLearning curve analysis
list_methodList all available methods
log_messagePrint a timestamped and indented log message
modeGet the most common value
modeling_procedureSetup a modeling procedure
na_indexSupport function for identifying missing values
name_procedureGet names for modeling procedures
neg_gmpaNegative geometric mean of class specific predictive accuracy
nice_axisPlots an axis the way an axis should be plotted.
nice_boxPlots a box around a plot
nice_requireLoad a package and offer to install if missing
notify_oncePrint a warning message if not printed earlier
pipePipe operator
plot.learning_curvePlot results from learning curve analysis
plot.SurvPlot Surv vector
predict_caretPredict using a 'caret' method
predict_cforestPredict with conditional inference forest
predict_coxphPredict using Cox proportional hazards model
predict_glmnetPredict using generalized linear model with elastic net...
predict_ldaPrediction using already trained prediction model
predict_lmPrediction using linear model
predict.modelPredict the response of unknown observations
predict_naive_bayesPredict using naive Bayes model
predict_pamrPrediction using nearest shrunken centroids.
predict_qdaPrediction using already trained classifier.
predict_randomForestPrediction using random forest.
predict_rpartPredict using a fitted decision tree
predict_svmPredict using support vector machine
pre_factor_to_logicalConvert factors to logical columns
pre_imputeBasic imputation
pre_impute_dfImpute a data frame
pre_impute_knnNearest neighbors imputation
pre_log_messagePrint log message during pre-processing
pre_pamrPAMR adapted dataset pre-processing
pre_processData preprocessing
print.preprocessed_dataPrint method for pre-processed data
pvalueExtraction of p-value from a statistical test
pvalue.coxphExtract p-value from a Cox proportional hazards model
pvalue.crrExtracts p-value from a competing risk model
pvalue.cumincExtract p-value from a cumulative incidence estimation
pvalue.survdiffExtracts p-value from a logrank test
resampleResampling schemes
roc_curveCalculate ROC curves
select'emil' and 'dplyr' integration
subresampleGenerate resampling subschemes
subtreeExtract a subset of a tree of nested lists
trivial_error_rateCalculate the trivial error rate
tuneTune parameters of modeling procedures
validate_dataValidate a pre-processed data set
vlinesAdd vertical or horizontal lines to a plot
weighted_error_rateWeighted error rate
emil documentation built on July 6, 2017, 9:01 a.m.