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⨍ Functions 400◇ Types & classes 80

Functionmultinomial_nb_algorithm_available_when_enabled

tests/classification.rs:79

Functionmultinomial_nb_rejects_fractional_features

tests/classification.rs:329

Functionmultinomial_nb_rejects_negative_features

tests/classification.rs:349

Functionmultinomial_nb_requires_settings

src/algorithms/classification.rs:1375

Functionmultinomial_nb_trains_and_predicts_with_non_negative_integers

tests/classification.rs:307

(row: usize, column: usize, source: ParseFloatError)

src/utils/io.rs:252

Create a new clustering model.

src/model/clustering.rs:42

src/model/preprocessing.rs:73

Create a new supervised model.

src/model/supervised.rs:141

src/settings/preprocessing.rs:333

(settings: &SVCParameters)

src/algorithms/classification.rs:275

(settings: &SVRParameters)

src/algorithms/regression.rs:44

(drop_first: bool)

src/settings/preprocessing.rs:268

Functionpipelines_support_composed_steps

tests/preprocessing.rs:140

Functionpolynomial_adds_squared_and_cross_terms

tests/features.rs:17

Functionpolynomial_errors_on_empty_input

tests/features.rs:34

Functionpower_transforms_apply_log_and_box_cox

tests/preprocessing.rs:98

Predict using the best-performing model. # Errors Returns [`ModelError::NotTrained`] if no algorithm has been trained or if inference fails.

src/model/supervised.rs:178

Predict cluster assignments

src/algorithms/clustering.rs:119

Functionpredict_requires_training

tests/classification.rs:137

Functionpredict_without_training_returns_error

tests/clustering.rs:171

Methodpreprocessing_failed

(err: &SettingsError)

src/model/supervised.rs:211

Functionprint_knn_search_algorithm_cover_tree

tests/display.rs:104

Functionprint_knn_search_algorithm_linear_search

tests/display.rs:92

Functionprint_knn_weight_function_distance

tests/display.rs:80

Functionprint_knn_weight_function_uniform

tests/display.rs:68

Functionprint_option_returns_none_for_none

tests/display.rs:20

Functionprint_option_returns_value_for_some

tests/display.rs:8

Functionrandom_forest_section_labels_n_trees

tests/settings_display.rs:19

Functionregression_builder_delegates

tests/supervised_settings.rs:15

Functionregression_metric_not_set_returns_error

tests/settings_error.rs:19

Functionregression_metric_unsupported_returns_error

tests/settings_error.rs:27

Functionregression_polynomial_preprocessing_predicts

tests/regression.rs:238

Functionregression_standardize_pipeline_predicts

tests/regression.rs:268

Functionrobust_scaling_centers_by_median

tests/preprocessing.rs:38

Methodrobust_stats

( data: &InputArray, column: usize, params: &RobustScaleParams, )

src/model/preprocessing.rs:864

Functionseparates_features_and_target

tests/load_labeled_csv.rs:5

Methodserialize

(&self, serializer: S)

src/settings/common.rs:36

Methodserialize

(&self, serializer: S)

src/settings/classification_settings.rs:241

Methodserialize

(&self, serializer: S)

src/settings/regression_settings.rs:421

Methodshuffle_data

(mut self, shuffle: bool)

src/settings/common.rs:277

Methodshuffle_data

(self, shuffle: bool)

src/settings/classification_settings.rs:141

Methodshuffle_data

(self, shuffle: bool)

src/settings/regression_settings.rs:210

Methodsorted_by

(mut self, sort_by: Metric)

src/settings/common.rs:332

Methodsorted_by

(self, sort_by: Metric)

src/settings/classification_settings.rs:200

Methodsorted_by

(self, sort_by: Metric)

src/settings/regression_settings.rs:276

src/utils/io.rs:33

Methodsupervised

src/settings/classification_settings.rs:219

Methodsupervised_mut

src/settings/classification_settings.rs:223

Functionsupport_vector_classifier_algorithm_available_when_enabled

tests/classification.rs:105

Functionsupport_vector_classifier_requires_settings

tests/classification.rs:288

Functionsupport_vector_classifier_trains_and_predicts

tests/classification.rs:151

Functiontest_all_algorithms_included

tests/classification.rs:29

Functiontest_default_classification

tests/classification.rs:19

Functiontest_default_regression

tests/regression.rs:15

Functiontest_extra_trees_missing_settings_error

tests/regression.rs:105

Functiontest_extra_trees_regression_trains_successfully

tests/regression.rs:58

Functiontest_extra_trees_skiplist_controls_algorithms

tests/regression.rs:84

Functiontest_knn_only_regression

tests/regression.rs:21

Functiontest_svr_missing_settings_error

tests/regression.rs:146

Functiontest_svr_regression_multiple_kernels

tests/regression.rs:36

Functiontest_svr_skiplist_controls_algorithms

tests/regression.rs:124

Functiontest_xgboost_invalid_parameters_error

tests/regression.rs:185

Functiontest_xgboost_regression_trains_successfully

tests/regression.rs:159

Functiontest_xgboost_skiplist_controls_algorithms

tests/regression.rs:217

Methodto_classifier_params

Convert to smartcore KNN classifier parameters using the configured distance metric. # Errors Returns [`DistanceError::UnsupportedDistance`] if the

src/settings/knn_parameters.rs:54

Methodto_regressor_params

Convert to smartcore KNN regressor parameters using the configured distance metric. # Errors Returns [`DistanceError::UnsupportedDistance`] if the c

src/settings/knn_parameters.rs:77

Train all available algorithms and record their performance. # Errors Returns [`Failed`] if cross-validation fails for any algorithm.

src/model/supervised.rs:158

( model: DenseBernoulliNB<INPUT, OUTPUT, OutputArray>, binarize: Option<INPUT>, )

src/algorithms/classification.rs:476

(distance: Distance)

src/utils/distance/mod.rs:74

Methoduntrained

src/algorithms/classification.rs:469

(mut self, verbose: bool)

src/settings/common.rs:288

(self, verbose: bool)

src/settings/classification_settings.rs:153

(mut self, verbose: bool)

src/settings/clustering_settings.rs:106

(self, verbose: bool)

src/settings/regression_settings.rs:224

Methodvisit_map

(self, mut map: A)

src/settings/common.rs:111

Methodvisit_map

(self, mut map: A)

src/settings/classification_settings.rs:344

Methodvisit_map

(self, mut map: A)

src/settings/regression_settings.rs:510

Methodvisit_str

(self, value: &str)

src/settings/common.rs:81

Methodvisit_str

(self, value: &str)

src/settings/classification_settings.rs:303

Methodvisit_str

(self, value: &str)

src/settings/regression_settings.rs:476

Methodwith_algorithm

(mut self, algorithm: ClusteringAlgorithmName)

src/settings/clustering_settings.rs:89

(mut self, c: f32)

src/settings/svc_parameters.rs:28

(mut self, eps: f64)

src/settings/clustering_settings.rs:75

Methodwith_feature_range

(mut self, range: (f64, f64))

src/settings/preprocessing.rs:176

Methodwith_final_model

(mut self, approach: FinalAlgorithm)

src/settings/common.rs:321

Methodwith_final_model

(self, approach: FinalAlgorithm)

src/settings/classification_settings.rs:188

Methodwith_final_model

(self, approach: FinalAlgorithm)

src/settings/regression_settings.rs:262

(mut self, k: usize)

src/settings/clustering_settings.rs:61

Methodwith_kernel

(mut self, kernel: Kernel)

src/settings/svc_parameters.rs:42

Methodwith_mean

(mut self, with_mean: bool)

src/settings/preprocessing.rs:44

Methodwith_number_of_folds

(mut self, n: usize)

src/settings/common.rs:266

Methodwith_number_of_folds

(self, n: usize)

src/settings/classification_settings.rs:128

Methodwith_number_of_folds

(self, n: usize)

src/settings/regression_settings.rs:195

Methodwith_preprocessing

(mut self, pre: PreprocessingPipeline)

src/settings/common.rs:299

Methodwith_preprocessing

(self, pre: PreprocessingPipeline)

src/settings/classification_settings.rs:169

Methodwith_preprocessing

(self, pre: PreprocessingPipeline)

src/settings/regression_settings.rs:242

Methodwith_quantile_range

(mut self, range: (f64, f64))

src/settings/preprocessing.rs:200

(mut self, with_std: bool)

src/settings/preprocessing.rs:51

(mut self, tol: f32)

src/settings/svc_parameters.rs:35

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