assess | R Documentation |
Assesses how well an sboost classifier classifies the data.
assess(object, features, outcomes, include_scores = FALSE)
object |
sboost_classifier S3 object output from sboost. |
features |
feature set data.frame. |
outcomes |
outcomes corresponding to the features. |
include_scores |
if true feature_scores are included in output. |
An sboost_assessment S3 object containing:
Last row of cumulative statistics (i.e. when all stumps are included in assessment).
stump - the index of the last decision stump added to the assessment.
true_positive - number of true positive predictions.
false_negative - number of false negative predictions.
true_negative - number of true negative predictions.
false_positive - number of false positive predictions.
prevalence - true positive / total.
accuracy - correct predictions / total.
sensitivity - correct predicted positive / true positive.
specificity - correct predicted negative / true negative.
ppv - correct predicted positive / predicted positive.
npv - correct predicted negative / predicted negative.
f1 - harmonic mean of sensitivity and ppv.
If include_scores is TRUE, for each feature in the classifier lists scores for each row in the feature set.
sboost sboost_classifier object used for assessment.
Shows which outcome was considered as positive and which negative.
Shows the parameters that were used for assessment.
sboost
documentation.
# malware malware_classifier <- sboost(malware[-1], malware[1], iterations = 5, positive = 1) assess(malware_classifier, malware[-1], malware[1]) # mushrooms mushroom_classifier <- sboost(mushrooms[-1], mushrooms[1], iterations = 5, positive = "p") assess(mushroom_classifier, mushrooms[-1], mushrooms[1])
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