mlr3measures v0.3.1

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Performance Measures for 'mlr3'

Implements multiple performance measures for supervised learning. Includes over 40 measures for regression and classification. Additionally, meta information about the performance measures can be queried, e.g. what the best and worst possible performances scores are.

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mlr3measures

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Implements multiple performance measures for supervised learning. Includes over 40 measures for regression and classification. Additionally, meta information about the performance measures can be queried, e.g. what the best and worst possible performances scores are. Internally, checkmate is used to check arguments efficiently - no other runtime dependencies.

The function reference gives an encompassing overview over implemented measures.

Note that explicitly loading this package is not required if you want to use any of these measures in mlr3. Also note that we advise against attaching the package via library() to avoid namespace clashes. Instead, load the namespace via requireNamespace() and use the :: operator.

Functions in mlr3measures

Name Description
bias Bias
binary_params Binary Classification Parameters
ce Classification Error
bacc Balanced Accuracy
bbrier Binary Brier Score
auc Area Under the ROC Curve
confusion_matrix Calculate Binary Confusion Matrix
dor Diagnostic Odds Ratio
acc Classification Accuracy
classif_params Classification Parameters
fpr False Positive Rate
fn False Negatives
ktau Kendall's tau
maxae Max Absolute Error
maxse Max Squared Error
mbrier Multiclass Brier Score
logloss Log Loss
ppv Positive Predictive Value
mae Mean Absolute Errors
mcc Matthews Correlation Coefficient
prauc Area Under the Precision-Recall Curve
mse Mean Squared Error
fdr False Discovery Rate
fbeta F-beta Score
medse Median Squared Error
smape Symmetric Mean Absolute Percent Error
fomr False Omission Rate
mlr3measures-package mlr3measures: Performance Measures for 'mlr3'
mape Mean Absolute Percent Error
mauc_aunu Multiclass AUC Scores
fp False Positives
tnr True Negative Rate
pbias Percent Bias
tp True Positives
npv Negative Predictive Value
rmsle Root Mean Squared Log Error
rmse Root Mean Squared Error
rae Relative Absolute Error
sse Sum of Squared Errors
tn True Negatives
regr_params Regression Parameters
rrse Root Relative Squared Error
rse Relative Squared Error
msle Mean Squared Log Error
tpr True Positive Rate
measures Measure Registry
rsq R Squared
medae Median Absolute Errors
fnr False Negative Rate
sae Sum of Absolute Errors
srho Spearman's rho
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License LGPL-3
URL https:///mlr3measures.mlr-org.com, https://github.com/mlr-org/mlr3measures
BugReports https://github.com/mlr-org/mlr3measures/issues
Encoding UTF-8
Config/testthat/edition 3
RoxygenNote 7.1.1
Collate 'assertions.R' 'bibentries.R' 'measures.R' 'binary_auc.R' 'binary_bbrier.R' 'binary_dor.R' 'binary_fbeta.R' 'binary_fdr.R' 'binary_fn.R' 'binary_fnr.R' 'binary_fomr.R' 'binary_fp.R' 'binary_fpr.R' 'binary_mcc.R' 'binary_npv.R' 'binary_ppv.R' 'binary_prauc.R' 'binary_tn.R' 'binary_tnr.R' 'binary_tp.R' 'binary_tpr.R' 'classif_acc.R' 'classif_auc.R' 'classif_bacc.R' 'classif_ce.R' 'classif_logloss.R' 'classif_mbrier.R' 'confusion_matrix.R' 'helper.R' 'regr_bias.R' 'regr_ktau.R' 'regr_mae.R' 'regr_mape.R' 'regr_maxae.R' 'regr_maxse.R' 'regr_medae.R' 'regr_medse.R' 'regr_mse.R' 'regr_msle.R' 'regr_pbias.R' 'regr_rae.R' 'regr_rmse.R' 'regr_rmsle.R' 'regr_rrse.R' 'regr_rse.R' 'regr_rsq.R' 'regr_sae.R' 'regr_smape.R' 'regr_srho.R' 'regr_sse.R' 'roxygen.R' 'zzz.R'
NeedsCompilation no
Packaged 2021-01-05 19:51:29 UTC; michel
Repository CRAN
Date/Publication 2021-01-06 16:00:37 UTC

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