mlr3-package | mlr3: Machine Learning in R - Next Generation |
as_benchmark_result | Convert to BenchmarkResult |
as_benchmark_result.ResampleResult | Convert to BenchmarkResult |
as_data_backend | Create a Data Backend |
as_data_backend.data.frame | Create a Data Backend |
as_data_backend.Matrix | Create a Data Backend |
as_learner | Object Coercion |
as_learner.Learner | Object Coercion |
as_learners | Object Coercion |
as_learners.Learner | Object Coercion |
as_learners.list | Object Coercion |
as_measure | Object Coercion |
as_measure.Measure | Object Coercion |
as_measure.NULL | Object Coercion |
as_measures | Object Coercion |
as_measures.list | Object Coercion |
as_measures.Measure | Object Coercion |
as_measures.NULL | Object Coercion |
as_resampling | Object Coercion |
as_resampling.Resampling | Object Coercion |
as_resamplings | Object Coercion |
as_resamplings.list | Object Coercion |
as_resamplings.Resampling | Object Coercion |
as_task | Object Coercion |
as_task.Task | Object Coercion |
as_tasks | Object Coercion |
as_tasks.list | Object Coercion |
as_tasks.Task | Object Coercion |
benchmark | Benchmark Multiple Learners on Multiple Tasks |
BenchmarkResult | Container for Benchmarking Results |
benchmark_grid | Generate a Benchmark Grid Design |
DataBackend | DataBackend |
DataBackendDataTable | DataBackend for data.table |
DataBackendMatrix | DataBackend for Matrix |
default_measures | Get a Default Measure |
Learner | Learner Class |
LearnerClassif | Classification Learner |
LearnerClassifDebug | Classification Learner for Debugging |
LearnerClassifFeatureless | Featureless Classification Learner |
LearnerClassifRpart | Classification Tree Learner |
LearnerRegr | Regression Learner |
LearnerRegrFeatureless | Featureless Regression Learner |
LearnerRegrRpart | Regression Tree Learner |
lrn | Syntactic Sugar for Object Construction |
lrns | Syntactic Sugar for Object Construction |
Measure | Measure Class |
MeasureClassif | Classification Measure |
MeasureClassifCosts | Cost-sensitive Classification Measure |
MeasureDebug | Debug Measure |
MeasureElapsedTime | Elapsed Time Measure |
MeasureOOBError | Out-of-bag Error Measure |
MeasureRegr | Regression Measure |
MeasureSelectedFeatures | Selected Features Measure |
mlr3 | mlr3: Machine Learning in R - Next Generation |
mlr_coercions | Object Coercion |
mlr_learners | Dictionary of Learners |
mlr_learners_classif.debug | Classification Learner for Debugging |
mlr_learners_classif.featureless | Featureless Classification Learner |
mlr_learners_classif.rpart | Classification Tree Learner |
mlr_learners_regr.featureless | Featureless Regression Learner |
mlr_learners_regr.rpart | Regression Tree Learner |
mlr_measures | Dictionary of Performance Measures |
mlr_measures_classif.acc | Classification Accuracy |
mlr_measures_classif.auc | Area Under the ROC Curve |
mlr_measures_classif.bacc | Balanced Accuracy |
mlr_measures_classif.ce | Classification Error |
mlr_measures_classif.costs | Cost-sensitive Classification Measure |
mlr_measures_classif.dor | Diagnostic Odds Ratio |
mlr_measures_classif.fbeta | F-beta Score |
mlr_measures_classif.fdr | False Discovery Rate |
mlr_measures_classif.fn | False Negatives |
mlr_measures_classif.fnr | False Negative Rate |
mlr_measures_classif.fomr | False Omission Rate |
mlr_measures_classif.fp | False Positives |
mlr_measures_classif.fpr | False Positive Rate |
mlr_measures_classif.logloss | Log Loss |
mlr_measures_classif.mcc | Matthews Correlation Coefficient |
mlr_measures_classif.npv | Negative Predictive Value |
mlr_measures_classif.ppv | Positive Predictive Value |
mlr_measures_classif.precision | Positive Predictive Value |
mlr_measures_classif.recall | True Positive Rate |
mlr_measures_classif.sensitivity | True Positive Rate |
mlr_measures_classif.specificity | True Negative Rate |
mlr_measures_classif.tn | True Negatives |
mlr_measures_classif.tnr | True Negative Rate |
mlr_measures_classif.tp | True Positives |
mlr_measures_classif.tpr | True Positive Rate |
mlr_measures_debug | Debug Measure |
mlr_measures_elapsed_time | Elapsed Time Measure |
mlr_measures_oob_error | Out-of-bag Error Measure |
mlr_measures_regr.bias | Bias |
mlr_measures_regr.ktau | Kendall's tau |
mlr_measures_regr.mae | Mean Absolute Errors |
mlr_measures_regr.mape | Mean Absolute Percent Error |
mlr_measures_regr.maxae | Max Absolute Error |
mlr_measures_regr.medae | Median Absolute Errors |
mlr_measures_regr.medse | Median Squared Error |
mlr_measures_regr.mse | Mean Squared Error |
mlr_measures_regr.msle | Mean Squared Log Error |
mlr_measures_regr.pbias | Percent Bias |
mlr_measures_regr.rae | Relative Absolute Error |
mlr_measures_regr.rmse | Root Mean Squared Error |
mlr_measures_regr.rmsle | Root Mean Squared Log Error |
mlr_measures_regr.rrse | Root Relative Squared Error |
mlr_measures_regr.rse | Relative Squared Error |
mlr_measures_regr.rsq | R Squared |
mlr_measures_regr.sae | Sum of Absolute Errors |
mlr_measures_regr.smape | Symmetric Mean Absolute Percent Error |
mlr_measures_regr.srho | Spearman's rho |
mlr_measures_regr.sse | Sum of Squared Errors |
mlr_measures_selected_features | Selected Features Measure |
mlr_measures_time_both | Elapsed Time Measure |
mlr_measures_time_predict | Elapsed Time Measure |
mlr_measures_time_train | Elapsed Time Measure |
mlr_resamplings | Dictionary of Resampling Strategies |
mlr_resamplings_bootstrap | Bootstrap Resampling |
mlr_resamplings_custom | Custom Resampling |
mlr_resamplings_cv | Cross Validation Resampling |
mlr_resamplings_holdout | Holdout Resampling |
mlr_resamplings_repeated_cv | Repeated Cross Validation Resampling |
mlr_resamplings_subsampling | Subsampling Resampling |
mlr_sugar | Syntactic Sugar for Object Construction |
mlr_tasks | Dictionary of Tasks |
mlr_tasks_boston_housing | Boston Housing Regression Task |
mlr_tasks_german_credit | German Credit Classification Task |
mlr_tasks_iris | Iris Classification Task |
mlr_tasks_mtcars | Motor Trend Regression Task |
mlr_tasks_pima | Pima Indian Diabetes Classification Task |
mlr_tasks_sonar | Sonar Classification Task |
mlr_tasks_spam | Spam Classification Task |
mlr_tasks_wine | Wine Classification Task |
mlr_tasks_zoo | Zoo Classification Task |
mlr_task_generators | Dictionary of Task Generators |
mlr_task_generators_2dnormals | 2D Normals Classification Task Generator |
mlr_task_generators_friedman1 | Friedman1 Regression Task Generator |
mlr_task_generators_smiley | Smiley Classification Task Generator |
mlr_task_generators_xor | XOR Classification Task Generator |
msr | Syntactic Sugar for Object Construction |
msrs | Syntactic Sugar for Object Construction |
predict.Learner | Predict Method for Learners |
Prediction | Abstract Prediction Object |
PredictionClassif | Prediction Object for Classification |
PredictionRegr | Prediction Object for Regression |
resample | Resample a Learner on a Task |
ResampleResult | Container for Results of 'resample()' |
Resampling | Resampling Class |
ResamplingBootstrap | Bootstrap Resampling |
ResamplingCustom | Custom Resampling |
ResamplingCV | Cross Validation Resampling |
ResamplingHoldout | Holdout Resampling |
ResamplingRepeatedCV | Repeated Cross Validation Resampling |
ResamplingSubsampling | Subsampling Resampling |
rsmp | Syntactic Sugar for Object Construction |
rsmps | Syntactic Sugar for Object Construction |
Task | Task Class |
TaskClassif | Classification Task |
TaskGenerator | TaskGenerator Class |
TaskGenerator2DNormals | 2D Normals Classification Task Generator |
TaskGeneratorFriedman1 | Friedman1 Regression Task Generator |
TaskGeneratorSmiley | Smiley Classification Task Generator |
TaskGeneratorXor | XOR Classification Task Generator |
TaskRegr | Regression Task |
tgen | Syntactic Sugar for Object Construction |
tgens | Syntactic Sugar for Object Construction |
tsk | Syntactic Sugar for Object Construction |
tsks | Syntactic Sugar for Object Construction |