Gram Matrix

Given a data matrix $XX$ whose rows are samples and whose columns are features, compute the Gram matrix $X^{\mathrm{\top }}XX^\backslash top\; X$ of its columns.

Implement solve(X).

Returns. Return a symmetric NumPy array of shape $(d,d)(d,\; d)$ for $dd$ columns.

Examples

Example 1

Input:

solve([[1.0, 2.0], [3.0, 4.0]])

Output:

[[10.0, 14.0], [14.0, 20.0]]

Example 2

Input:

solve([[1.0, 0.0], [0.0, 1.0]])

Output:

[[1.0, 0.0], [0.0, 1.0]]