Hi everyone
I'm quite new to Knime. I have a dataset like this
+-------+-------+---------+-------+ | class | shape | surface | color | +-------+-------+---------+-------+ | e | f | k | w | | e | f | b | y | | t | k | s | w | | e | s | f | u | +-------+-------+---------+-------+
I want to mine frequents characteristics and association rules over records.
For example, rules like: shape.f => color.w, surface.s
The "problem" is that, in this dataset, the same letter value can represent really different things. surface.s = smooth but shape.s = sunken .
I can't merge all columns in a single with a Create Collection Column and run an Association Rule Learner because i will loose the column meaning of each letter.
A solution would be to build a column like the follwing one, and run the Association Rule Learner on it but i don't know how to do this.
+------------------------------+ | merged_attributes | +------------------------------+ | [shape.f, surface.k,color.w] | | [shape.f, surface.b,color.y] | | [shape.k, surface.s,color.w] | | [shape.s, surface.f,color.u] | +------------------------------+
Thank you for your help.
Best regards.