Man pages for SchlossLab/mikropml
User-Friendly R Package for Supervised Machine Learning Pipelines

calc_perf_metricsGet performance metrics for test data
combine_hp_performanceCombine hyperparameter performance metrics for multiple...
define_cvDefine cross-validation scheme and training parameters
get_caret_processed_dfGet preprocessed dataframe for continuous variables
get_feature_importanceGet feature importance using the permutation method
get_hp_performanceGet hyperparameter performance metrics
get_hyperparams_listSet hyperparameters based on ML method and dataset...
get_outcome_typeGet outcome type.
get_partition_indicesSelect indices to partition the data into training & testing...
get_perf_metric_fnGet default performance metric function
get_perf_metric_nameGet default performance metric name
get_performance_tblGet model performance metrics as a one-row tibble
get_tuning_gridGenerate the tuning grid for tuning hyperparameters
group_correlated_featuresGroup correlated features
keep_groups_in_cv_partitionsWhether groups can be kept together in partitions during...
mikropmlmikropml: User-Friendly R Package for Robust Machine Learning...
otu_mini_binMini OTU abundance dataset
otu_mini_bin_results_glmnetResults from running the pipline with L2 logistic regression...
otu_mini_bin_results_rfResults from running the pipline with random forest on...
otu_mini_bin_results_rpart2Results from running the pipline with rpart2 on...
otu_mini_bin_results_svmRadialResults from running the pipline with svmRadial on...
otu_mini_bin_results_xgbTreeResults from running the pipline with xbgTree on...
otu_mini_cont_results_glmnetResults from running the pipeline with glmnet on...
otu_mini_cont_results_nocvResults from running the pipeline with glmnet on...
otu_mini_cvCross validation on 'train_data_mini' with grouped features.
otu_mini_multiMini OTU abundance dataset with 3 categorical variables
otu_mini_multi_groupGroups for otu_mini_multi
otu_mini_multi_results_glmnetResults from running the pipeline with glmnet on...
otu_smallSmall OTU abundance dataset
plot_hp_performancePlot hyperparameter performance metrics
plot_model_performancePlot performance metrics for multiple ML runs with different...
preprocess_dataPreprocess data prior to running machine learning
randomize_feature_orderRandomize feature order to eliminate any position-dependent...
reexportsdplyr pipe
remove_singleton_columnsRemove columns appearing in only 'threshold' row(s) or fewer.
replace_spacesReplace spaces in all elements of a character vector with...
run_mlRun the machine learning pipeline
tidy_perf_dataTidy the performance dataframe
train_modelTrain model using 'caret::train()'.
SchlossLab/mikropml documentation built on Nov. 25, 2021, 1:13 p.m.