def __init__(self,
trainRecords,
anomalyThreshold,
cacheSize,
classificationVectorType=1,
activeColumnCount=40,
classificationMaxDist=0.30,
**classifierArgs):
# Internal Region Values
self._maxLabelOutputs = 16
self._activeColumnCount = activeColumnCount
self._prevPredictedColumns = numpy.array([])
self._anomalyVectorLength = None
self._classificationMaxDist = classificationMaxDist
self._iteration = 0
# Set to create deterministic classifier
classifierArgs['SVDDimCount'] = None
# Parameters
self.trainRecords = trainRecords
self.anomalyThreshold = anomalyThreshold
self.cacheSize = cacheSize
self.classificationVectorType = classificationVectorType
self._knnclassifierArgs = classifierArgs
self._knnclassifier = KNNClassifierRegion(**self._knnclassifierArgs)
self.labelResults = []
self.saved_categories = []
self._recordsCache = []
self._version = KNNAnomalyClassifierRegion.__VERSION__
def __setstate__(self, state):
"""
Set the state of ourself from a serialized state.
"""
if '_version' not in state or state['_version'] == 1:
knnclassifierProps = state.pop('_knnclassifierProps')
self.__dict__.update(state)
self._knnclassifier = KNNClassifierRegion(**self._knnclassifierArgs)
self._knnclassifier.__setstate__(knnclassifierProps)
self._version = KNNAnomalyClassifierRegion.__VERSION__
else:
raise Exception("Invalid KNNAnomalyClassifierRegion version. Current "
"version: %s" % (KNNAnomalyClassifierRegion.__VERSION__))
