Each point on the ROC curve represents a separate confusion matrix. The test checks if there is a significant difference between the counts in these two cells. caret-internal: Internal Functions caretSBF: Selection By Filtering (SBF) Helper Functions cars: Kelly Blue Book resale data for 2005 model year GM cars classDist: Compute and predict the distances to class centroids confusionMatrix: Create a confusion matrix ain: Estimate a Resampled Confusion Matrix cox2: COX-2. Specifically, the No/Yes and Yes/No (A/B and B/A in your case) cells in the confusion matrix. McNemar’s Test captures the errors made by both models. Area under the ROC Curve (AUC) curve is called AUC. Interpret the McNemar’s Test for Classifiers.
In such cases, relying only on accuracy will not give the real picture as the model which did not predict 'no' also did pretty well on accuracy measure. For example, in a binary classification involving 50 actual 'yes' and 5 actual 'no', a model which classifies every observation as 'yes' is also having an accuracy level of 90%. R-release (arm64): ConfusionTableR_1.0.4.tgz, r-oldrel (arm64): ConfusionTableR_1.0.4.tgz, r-release (x86_64): ConfusionTableR_1.0.4.tgz, r-oldrel (x86_64): ConfusionTableR_1.0.4.Accuracy alone is not a useful measure whenever there is class imbalance. R-devel: ConfusionTableR_1.0.4.zip, r-release: ConfusionTableR_1.0.4.zip, r-oldrel: ConfusionTableR_1.0.4.zip Knitr, rmarkdown, e1071, randomForest, scales, mlbench, FeatureTerminatoR Version:ĭplyr, tidyr, magrittr, caret, purrr, furrr Traditionally, this approach has been used for highlighting model representation and feature slippage. This is useful, as it allows quick conversion of these objects for storage in database systems and to track ML model performance over time. This tool works with classification problems for binary and multi-classification problems and allows for the record level conversion of the confusion matrix outputs. The intended usage is to allow the tool to work with the outputs of machine learning classification models. Takes the outputs of a 'caret' confusion matrix and allows for the quick conversion of these list items to lists. ConfusionTableR: Confusion Matrix Toolset confusionMatrix function - RDocumentation caret (version 6.0-93) confusionMatrix: Create a confusion matrix Description Calculates a cross-tabulation of observed and predicted classes with associated statistics.