def calculatePredictions(learnTreeGenerator, docs1, docs2, predictionRatio1, predictionRatio2):
numDocuments1 = len(docs1)
numDocuments2 = len(docs2)
for learnTree in learnTreeGenerator:
numCorrectPredictionDocs1 = 0
numCorrectPredictionDocs2 = 0
for doc in docs1:
prediction = DTN.predict(learnTree, doc)
if prediction == doc[-1]:
# if the prediction was correct
numCorrectPredictionDocs1+= 1
for doc in docs2:
prediction = DTN.predict(learnTree, doc)
if prediction == doc[-1]:
numCorrectPredictionDocs2+= 1
predictionRatio1.append(numCorrectPredictionDocs1/numDocuments1 * 100)
predictionRatio2.append(numCorrectPredictionDocs2/numDocuments2 * 100)
def __init__(self, dataset, features, mode):
self.dTree = DTN.computeFirstNode(dataset, features, mode)
self.mode = mode
