Classification and Regression Tests


[Up] [Top]

Documentation for package ‘crtests’ version 0.2.1

Help Pages

crtests-package crtests: A package for creating and executing classification and regression tests
apply_levels Converts the column factor levels in 'df' to those in 'df_reference'
argument_match_test Test function with non-matching arguments
capitalize_first Capitalize the first letter of a word
classification_model Generic function for creating a classification model
classification_model.boosting Generic function for creating a classification model
classification_model.default Generic function for creating a classification model
classification_model.rpart Generic function for creating a classification model
createtest Create a classification or regression test case
create_and_run_test Create test and run it
crtests crtests: A package for creating and executing classification and regression tests
drop_na Remove NAs according to a strategy
evaluate Evaluate the performance of a prediction.
evaluate_problem Generic function for evaluation of test results
evaluate_problem.classification Generic function for evaluation of test results
evaluate_problem.regression Generic function for evaluation of test results
evaluation Create an evaluation object
extract_formula Extract a formula from a test
factor_length Determine the length of the factors in a data.frame
group_levels Group infrequent levels in 'data', either a factor or a data.frame
group_levels.data.frame Group infrequent levels in 'data', either a factor or a data.frame
group_levels.default Group infrequent factor levels
group_levels.factor Group infrequent levels in 'data', either a factor or a data.frame
group_levels.list Group infrequent levels in 'data', either a factor or a data.frame
is_complete_row Determine if the rows in a data.frame have NAs
make_predictions Make predictions using a model Generic function for testing a model by making predictions
make_predictions.boosting Make predictions using a model Generic function for testing a model by making predictions
make_predictions.default Make predictions using a model Generic function for testing a model by making predictions
make_predictions.gbm Make predictions using a model Generic function for testing a model by making predictions
make_predictions.rpart Make predictions using a model Generic function for testing a model by making predictions
method_prepare Method-specific data preparation
method_prepare.default Method-specific data preparation
method_prepare.randomForest Method-specific data preparation
missing_argument_test Utility functions
multisample Make multiple samples of data
multisample.cross_fold Make multiple samples of data
multisample.random Make multiple samples of data
multitest Create and run multiple instances of a test
multitest_evaluation Create an evaluation of multiple tests
na_count Count the number of NAs in an object
na_count.data.frame Count the number of NAs in an object
na_count.default Count the number of NAs in an object
prepare Prepare the data for the specified test.
prepare.default Prepare the data for the specified test.
prepare_data Prepare data for training or testing.
print.evaluation Print an 'evaluation' object
print.multitest_evaluation Print a multitest_evaluation
print.multitest_evaluation.summary Print a multitest_evaluation.summary object
random_string Generate a random string
regression_model Fit a regression model Generic function for fitting a regression model
regression_model.default Fit a regression model Generic function for fitting a regression model
remove_names Set any names of x to ""
remove_names.matrix Set any names of x to ""
replace_names Replace strings in the names of an object
replace_names.data.frame Replace strings in the names of an object
replace_names.default Replace strings in the names of an object
replace_names.matrix Replace strings in the names of an object
runtest Run a classification or regression test
runtest.default Run a classification or regression test
summary.evaluation Summary of an evaluation
summary.multitest_evaluation Make a summary of multiple test evaluations
train_model Train a classification or regression model
train_model.classification Train a classification or regression model
train_model.regression Train a classification or regression model
util Utility functions