Description Usage Arguments Value
This version is made for 5-label classification. Inputs are prediction probability matricesof two classifiers.
1 | avg.arit(mat1, mat2, label = train$popularity, iter = 101)
|
mat1 |
Matrix of first classifier class probabiliets. |
mat2 |
Matrix of second classifier class probabiliets. |
label |
True class labels. Default train set popularity column. |
iter |
Number of weight combinations, default 101 (0.01 increment) |
An ordered matrix with weight combinations and matching accuracies
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