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Many ml algorithms use a similar (or verbatim) same type of input. i.e. a matrix X that has samples along the rows with each column being a certain feature of the data, and column vector y that has labels indicating what class each sample belongs to in the case of classification, or output points in the case of regression.
To avoid rewriting the handling of this data for every ml module, maybe we can make a single interface (maybe MLInput?) that stores this information and is used as an input for the ml modules?
The text was updated successfully, but these errors were encountered:
Many
ml
algorithms use a similar (or verbatim) same type of input. i.e. a matrixX
that has samples along the rows with each column being a certain feature of the data, and column vectory
that has labels indicating what class each sample belongs to in the case of classification, or output points in the case of regression.To avoid rewriting the handling of this data for every
ml
module, maybe we can make a single interface (maybeMLInput
?) that stores this information and is used as an input for theml
modules?The text was updated successfully, but these errors were encountered: