The Classifier companion object provides a method for testing predictive models.
Attributes
- Companion
- trait
- Graph
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- Supertypes
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class Objecttrait Matchableclass Any
- Self type
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Classifier.type
Members list
Value members
Concrete methods
Downsample to reduce imbalance of classes, by returning the group indices and the probability for each group.
Downsample to reduce imbalance of classes, by returning the group indices and the probability for each group.
Value parameters
- ns
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the number of instances in downsample
- y
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the classification/response vector
Attributes
Partition the dataset into groups, e.g., to set up for downsampling, by returning each group's indices and frequency counts. Instances with the same classification 'y(i)' will be found in the 'i'th group.
Partition the dataset into groups, e.g., to set up for downsampling, by returning each group's indices and frequency counts. Instances with the same classification 'y(i)' will be found in the 'i'th group.
Value parameters
- y
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the classification/response vector
Attributes
Shift the z matrix so that the minimum value for each column equals zero.
Shift the z matrix so that the minimum value for each column equals zero.
Value parameters
- z
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the matrix to be shifted
Attributes
Test (in-sample) by training and testing on the FULL dataset. Test (out-of-sample) by training on the TRAINING set and testing on the TESTING set.
Test (in-sample) by training and testing on the FULL dataset. Test (out-of-sample) by training on the TRAINING set and testing on the TESTING set.
Value parameters
- check
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whether to check the assertion that the in-sample and out-of-sample results are in rough agreement (e.g., at 20%)
- ext
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the model subtype extension (e.g., indicating the transformation function used)
- mod
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the model to be used
Attributes
Return value counts calculated from the input data. May wish to call shiftToZero before calling this method.
Return value counts calculated from the input data. May wish to call shiftToZero before calling this method.
Value parameters
- z
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the matrix to be shifted
Attributes
Concrete fields
hyper-parameters for classifiers
hyper-parameters for classifiers