Naive Bayes Classification of multiple rows
Hello everyone,
I am making a naive bayes classification process for some data in RapidMiner. I have a training data to construct a model which has some thousands of rows in the following format.
label attribute attribute attribute attribute attribute attribute
When I want to classify another data which has 3 rows and has following format:
attribute attribute attribute attribute attribute attribute
In this case, everything runs normally and I get a prediction for each row according to naive bayes classification results. (in total I get 3 predictions)
But my question is following: What if I assume that these 3 rows belongs to same category and therefore, I want to get only 1 prediction in total by using these three rows. How can I manage that? Please help me.
I hope I could explain myself.
Thanks in advance,
iinnaanncc
I am making a naive bayes classification process for some data in RapidMiner. I have a training data to construct a model which has some thousands of rows in the following format.
label attribute attribute attribute attribute attribute attribute
When I want to classify another data which has 3 rows and has following format:
attribute attribute attribute attribute attribute attribute
In this case, everything runs normally and I get a prediction for each row according to naive bayes classification results. (in total I get 3 predictions)
But my question is following: What if I assume that these 3 rows belongs to same category and therefore, I want to get only 1 prediction in total by using these three rows. How can I manage that? Please help me.
I hope I could explain myself.
Thanks in advance,
iinnaanncc