def classification(classifier, context, blockList, decisions, scaler, returnQueue=None,
shot=True, leaveout=-1):
"""
Returns a classification, no propabilities.
"""
feature_line = getSingleFeatureLine(context, blockList, decisions, shot, leaveout)
class_from_file = feature_line.pop()
feature_line = scaler.transform(feature_line)
classification = classifier.predict(feature_line)
if returnQueue:
returnQueue.put(classification)
returnQueue.close()
return classification
def calculateDistributionAndClassification(classifier, context, blocks, decisions,
scaler, shot_or_cut=True,
returnQueue=None, leave_out_class=None):
"""
Calculates a distribution using the given classifier. From that distribution the
highest Value is selected as classification. Both distribution and classification
are returned.
"""
feature_line = getSingleFeatureLine(context, blocks, decisions, shot_or_cut,
leave_out_class=leave_out_class)
feature_line.pop()
feature_vector = scaler.transform(np.array([feature_line]))
distribution = classifier.predict_proba(feature_vector)
classification = distribution[0].tolist().index(max(distribution[0].tolist()))
#classification = int(classifier.predict(feature_vector)[0])
if returnQueue:
returnQueue.put((distribution, classification))
returnQueue.close()
return distribution, classification
