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I would like to use another type of data, not atomic data, as a feature for a prediction. Suppose I have a Table with those Features: - Column 1: Categorical - House - Column 2: Numerical - 23.22 - Column 3: A Vector - [ 12, 22, 32 ] - Column 4: A Tree - [ [ 2323, 2323 ],[2323, 2323] , [ Boolean, Categorical ] ] - Column 5: A List [ 122, Boolean ] I would like to predict/classify ... Columns 2 ... for example.... I am making a Software to automatically respond questions... Any type...like "Where Foo was Born ?" ... I first make a query to a search engine --->>> then I get some Text data as a Result. So I do all the Parsing Staff... Tagging, Stemming, Parsing, Splitting... My first approach was to make a table, each row with a line of text.. and a lot of Features...like ... First Word ... Tag of First Word.. Chunks, etc.. But with this approach I am missing the relationships between the Sentences. I would like to know if there is an algorithm that look inside the Tree Structures... Vectors... and make the relations and extract whatever is relevant for predicting/classifying. I rather know a library that does that then an algorithm that I have to implement... Thank you very much ! |
