Man pages for kmaurer/binsemble
| add_bin_features | Add bin centers for selected variables |
| bin_1d_by_def | Univariate binning |
| bin_by_iq_def | Iterative Quantile Binning New Data from defined bins |
| bin_dictator_weighted | Establish bin dictator weights |
| bin_index_finder_nest | Find bin index from R-tree structure |
| bin_nd | Make multidimensional binned data or bin definitions (for... |
| bin_nd_by_def | Bin new data based on n-dimensional binning definition |
| binned_testing | binned_testing |
| bin_test_by_train | Bin test data |
| bin_weighted | Model weights for "weight_type == "bin weighted" VERSION 2 |
| cv_cohorts | CV cohort generator |
| cv_preds | K-fold CV Predictions |
| cv_testing_all_ensembles | cv_testing_all_ensembles |
| eval_cv_test_results | eval_cv_test_results |
| eval_ensemble | Function to evaluated the ensemble test accuracy against... |
| eval_ensemble_members | Function to evaluated the ensemble test accuracy against... |
| hello | Hello, World! |
| iq_binned_testing | binned_testing |
| iterative_quant_bin | Iterative Quantile Binning |
| knn_weighted | Model weights for "weight_type == "knn" |
| majority_vote | Simple Majority Vote Counter |
| make_bin_feature_list_pairs | make_bin_feature_list_pairs |
| make_bin_list | Convert bin bounds data frame into R-tree structure using... |
| make_cv_cohorts | CV cohort additions |
| make_ensemble | Build a weighted ensemble list |
| make_feature_pair_df | Create feature pair data frame |
| make_model_list | Function for building model list given Weka names |
| make_model_metric_array | Model metric array for combination rules |
| make_model_metric_array_avgpost | Average posterior vote |
| make_model_metric_array_majvote | Majority vote |
| make_nbins_list | Function to create list of nbins vectors to put into tuning... |
| make_nbins_list_pairs | make_nbins_list_pairs |
| make_preds | Predict classes using member models |
| make_stack_matrix | Stack Matrix builder |
| make_train_bins_index | Make bin index |
| make_train_preds | Make training predictions from all models in ensemble |
| predictEnsemble | Predict using an ensemble classifier |
| quant_bin_1d | One-Dimensional Empirical Quantile Binning |
| RA | Function to calculate classifier accuracy based on confusion... |
| rect_bin_1d | Standard rectangular 1d binning |
| round_df | Create data frame with rounded number of trailing digits |
| stretch_iq_bins | Adding Tolerance Buffer to outermost bins from Iterative... |
| testing_all_ensembles | testing_all_ensembles |
| unbinned_testing | Exhaustively testing ensemble on new dataset |
| weighted | Model weights for "weight_type == "weighted" |
