object ConfusionFit
The ConfusionFit companion object records the indicies and labels for the
base Quality of Fit (QoF) measures for the classification techniques.
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- final def ##: Int
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- def fitLabel: Seq[String]
Return the labels for the Scalar Quality of Fit (QoF) measures.
- def fitLabel_v: Seq[String]
Return the labels for the Vector Quality of Fit (QoF) micro-measures.
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- def help: String
Return the help string that describes the Quality of Fit (QoF) measures provided by the
ConfusionFitclass.Return the help string that describes the Quality of Fit (QoF) measures provided by the
ConfusionFitclass. The QoF measures are divided into four groups: general, ordinary, micro (per class) vectors and means of the micro vectors. Ordinary are values of the last element in the micro vectors and can be interpreted as, say the precision for the last class value/label, e.g., y = hasCancer in {no, yes}, is the prcision of the 'yes' prediction and is most meaningful when the number of class values/labels (k) is 2.- See also
en.wikipedia.org/wiki/Precision_and_recall
en.wikipedia.org/wiki/Cohen%27s_kappa
- val index_acc: Int
- val index_f1: Int
- val index_f1_m: Int
- val index_f1_v: Int
- val index_kappa: Int
- val index_p: Int
- val index_p_m: Int
- val index_p_rSq: Int
- val index_p_v: Int
- val index_r: Int
- val index_r_m: Int
- val index_r_v: Int
- val index_s: Int
- val index_s_m: Int
- val index_s_v: Int
- val index_sse: Int
- val index_sst: Int
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- def qofStatTable: Array[Statistic]
Create a table to store statistics for QoF measures, where each row corresponds to the statistics on a particular QoF measure, e.g., 'acc'
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- def test(y: VectoI, yp: VectoI, k: Int = 2): Unit
Test and report the confusion matrix and associate QoF measures.
Test and report the confusion matrix and associate QoF measures.
- y
the actual class values
- yp
the predicted class values
- k
the number of class labels {0, 1, ... , k-1}
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