k_sample_transform¶
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hyppo.ksample.k_sample_transform(inputs, test_type='normal')¶ Computes a k-sample transform of the inputs.
For k groups, this creates two matrices, the first vertically stacks the inputs. In order to use this function, the inputs must have the same number of dimensions p and can have varying number of samples n. The second output is a label matrix the one-hoc encodes the groups. The outputs are thus
(N, p)and(N, k)where N is the total number of samples. In the case where the test a random forest based tests, it creates a(N, 1)where the entries are varlues from 1 to k based on the number of samples.- Parameters
inputs (
listofndarray) -- A list of the inputs. All inputs must be(n, p)where n is the number of samples and p is the number of dimensions. n can vary between samples, but p must be the same among all the samples.test_type (
{"normal", "rf"}, default:"normal") -- Whether to one-hoc encode the inputs ("normal") or use a one-dimensional categorical encoding ("rf").
- Returns