python for datascience
Question
why do have to use reshape(-1,1) or reshape(1,-1) for a single feature before fitting it to the model in sklearn library?
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Machine Learning
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Answers ( 2 )
the single feature array is nothing but a 1D-array. when a 1D-array is passed to sklearn library module it considers and indices of the rows so we need to make other than 1D-array so what reshape(-1,1) does data it creates an array of one column and undefined rows(-1 represent there can be any number of rows).
example:
a = [1,2,3]
//after reshape(-1,1) is applied
a = [[1],
[2],
[3]]
the single feature array is nothing but a 1D-array. when a 1D-array is passed to the sklearn library module it considers as indices of the rows. So, we need to make this array other than a 1D-array.when reshape(-1,1) is applied it creates an array of one column and with some rows(-1 represent there can be any number of rows).
example:
a = [1,2,3]
//after reshape(-1,1) is applied
a = [[1],
[2],
[3]]