lambda-ml.factorization
Unsupervised learning with non-negative matrix factorization.
Example usage:
(def data [[1 2 3] [4 5 6]])
(let [dims 2]
(-> (factorizations data dims)
(nth 300)
((fn [x] (map #(mapv vec %) x)))))
;;=> ([[0.20900693256125408 0.2000948450048419]
;;=> [0.8547267961216941 0.32426625588317753]]
;;=> [[4.601094573778913 3.4274218917618486 2.1966425686791777]
;;=> [0.20523936453382804 6.391048036139935 12.709895897835892]])
factorizations
(factorizations v dims)(factorizations v w h)Returns a lazy seq of factorizations of the input matrix v. For an m-by-n input matrix, each factorization is a pair of latent matrices with dimensions m-by-dims and dims-by-n.