Outlier measure for data
out = outlierMeasure(B,X)
out = outlierMeasure(B,X,'param1',val1,'param2',val2,...)
out = outlierMeasure(B,X) computes outlier
measures for predictors
X using trees in the ensemble
The method computes the outlier measure for a given observation by
taking an inverse of the average squared proximity between this observation
and other observations.
outlierMeasure then normalizes
these outlier measures by subtracting the median of their distribution,
taking the absolute value of this difference, and dividing by the
median absolute deviation. A high value of the outlier measure indicates
that this observation is an outlier.
You can supply the proximity matrix directly by using the
out = outlierMeasure(B,X,'param1',val1,'param2',val2,...) specifies
optional parameter name/value pairs:
|Flag indicating how to treat the |
|Vector of true class labels. True class labels can be either
a numeric vector, character matrix, or cell array of character vectors.
When you supply this parameter, the method performs the outlier calculation
for any observations using only other observations from the same class.
This parameter must specify one label for each observation (row)