1.3.5 Matrices from math/matrix🔗ℹ

A math/matrix matrix is unnamed data: its rows are the observations. A response can be a column matrix, a row matrix or a one-dimensional math/array array. (require glmnet) does not load math/matrix, so a program that does not use it does not wait for it to load.

The Quick Start of R’s glmnet fits glmnet(x, y) to the 100 × 20 matrix x and the response vector y of QuickStartExample, then predicts at new rows nx drawn at random. Here is the same fit, with x a math/matrix matrix and y a column matrix:

> (require math/matrix math/distributions glmnet/datasets)

> (define-values (qs-x qs-y) (quick-start-example))

> (define x (list*->matrix (design-matrix->rows qs-x)))

> (define y (->col-matrix qs-y))

> (matrix-shape x)

100 20

> (define fit (elnet-path x y))

> (coef fit #:lambda 0.1)

'#(0.15092807247412926    1.3205971945479142    0.0    0.6751102344847403    0.0    -0.8174115175489668    0.5214366714587341    0.004829335148616431    0.3194159167155697    0.0    0.0    0.14249851856673404    0.0    0.0    -1.0599787019192302    0.0    0.0    0.0    0.0    0.0    -1.0218737036830785)

> (random-seed 29)

> (define nx (build-matrix 5 20 (lambda (i j) (sample (normal-dist)))))

> (predict fit nx #:lambda '(0.1 0.05))

'((1.3062999979031626    2.0460482043995163    -0.3251741946880151    -1.9745626856083445    1.6552393883406682)   (1.387664042746005    2.126839326881185    -0.26250673336767805    -2.1506980670436624    1.8246177456688972))

> (equal? fit (elnet-path qs-x qs-y))

#t

Converting a large matrix takes time on every fit; convert it once with matrix->design-matrix and pass the design matrix to each fit (see The explicit route).