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Evaluation predictions of a classification model according to accuracy.
evaluation.accuracy(predictions, targets, ...)
The evaluation of the predictions (numeric value).
The predictions of a classification model (factor or vector).
factor
vector
Actual targets of the dataset (factor or vector).
Other parameters.
evaluation.fmeasure, evaluation.fowlkesmallows, evaluation.goodness, evaluation.jaccard, evaluation.kappa, evaluation.precision, evaluation.precision, evaluation.recall, evaluation
evaluation.fmeasure
evaluation.fowlkesmallows
evaluation.goodness
evaluation.jaccard
evaluation.kappa
evaluation.precision
evaluation.recall
evaluation
require (datasets) data (iris) d = splitdata (iris, 5) model.nb = NB (d$train.x, d$train.y) pred.nb = predict (model.nb, d$test.x) evaluation.accuracy (pred.nb, d$test.y)
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