Initially dataset contained some fields, in which some value in
the records was missing. These were identified and replaced
with most appropriate values using ReplaceMissingValues
filter from Weka 3.6.6. The ReplaceMissingValues filter scans
all records & replaces missing values with mean mode
method. This process is known as Data PreProcessing. After
pre-processing the data, data mining classification techniques
such as Neural Networks, Decision Trees, & Naive Bayes
were applied.
A confusion matrix is obtained to calculate the accuracy of
classification. A confusion matrix shows how many instances
have been assigned to each class. In our experiment we have
two classes, and therefore we have a 2x2 confusion matrix.