The problem is a multi-label classification problem. Now, I know how to train and classify using single row with several attributes. For example, if the dataset looks like the first table from the attached file. Here, each row is associated with a single label. Thus, I can train and test after separating the dataset into training and testing sets. But the problem occurs when classification label / target label depends on multiple rows such as the second table from the attached file. Consecutive N rows makes one category. Can you please guide me towards a solution?
- Is it possible to fit this problem in any existing tool? For example, WEKA or Neural network using Keras.
- Or do I have to change the algorithm in order to fit the problem! Is there any existing solution?
- Or do I need to modify the rows in such a way that it transforms into one?