I am new at statistics and ML. Due to my lack of theoretical background I was wandering if does it make sense to combine NBC and CC. I am participating to the kaggle competition https://www.kaggle.com/c/sf-crime and I have to classify a crime on the basis of a data set composed of those categories predict the type of crime:
(Dates,DayOfWeek,PdDistrict,Address,X,Y) ----> Type of crime
I would like to dump the X Y features and implement with the remaing a NBC. Then to capture the correlation among the variables create a graph for each crime category: the nodes would be the rows of the NBC and the weight of the links which represent occurrences in which those factors appeared together.
For example (Wednesday, prostitution 12.00 ingleside) will increase by one all the links among those nodes.
Once this is done I would like to compute the CC for each node and try for each new crime how it fits in those graphs summing up all the CC of the respective node. I would like to combine this result with the classification of NBC.
Does it makes sense? Does I am reinventing the wheel? If this method makes sense, is there a way to do it?