ComputeMetaFeaturesAll: Computes features from a dataset, but using 2 normalization...
In sevvandi/outselect: Algorithm selection for unsupervised outlier detection
Description
Usage
Arguments
Value
Examples
Description
Computes features from a dataset, but using 2 normalization methods: MIN_MAX and MEDIAN_IQR.
Usage
1
ComputeMetaFeaturesAll(dat.o)
Arguments
dat.o
This is the data with the last column named as outlier having values yes or no. All other columns are numeric. Non-numerical data need to be converted to numerical before computing features.
Value
The set of features.
Examples
1
2
3
data(Arrhythmia_withoutdupl_05_v05)
dat <- Arrhythmia_withoutdupl_05_v05
feat <- ComputeMetaFeaturesAll(dat)
sevvandi/outselect documentation built on June 1, 2019, 3:58 a.m.
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Description Usage Arguments Value Examples
Description
Computes features from a dataset, but using 2 normalization methods: MIN_MAX and MEDIAN_IQR.
Usage
1 | ComputeMetaFeaturesAll(dat.o)
|
Arguments
dat.o |
This is the data with the last column named as |
Value
The set of features.
Examples
1 2 3 | data(Arrhythmia_withoutdupl_05_v05)
dat <- Arrhythmia_withoutdupl_05_v05
feat <- ComputeMetaFeaturesAll(dat)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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