Q.1 Lift the measures to distance between K objects. The input is a numpy array that contains K rows…

Q.1 Lift the measures to distance between K objects. The input is a numpy array that contains K rows…

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Q.1 Lift the measures to distance between K objects. The input is a
numpy array that contains K rows and N columns. Compute pairwise
distances (or similarities) and place them into a single distance matrix.
You can assume that all values of the input matrix have the same type
(that you must check before applying the measures).
Q.2 Provide testing procedures for your solution in Question Select
numpy vectors of at least length 10 of different types and show distance
computations (the distance matrices you computed in Question ). Make
sure that in your tests you cover all types of attributes (nominal, binary,
ordinal, and numeric). Make sure to test the Minkowski distance for
different values of h.
Implement without assuming that all attributes of an object
have the same type.

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Answer rating: 100% (QA)

Answer import numpy as np from scipy spatial distance import cdist Function to compute pairwise dist
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