Classify MNIST with Random Forest Classifier

random-forest.hy

(import [tensorflow [keras]])
(import [numpy :as np])
(import [sklearn.ensemble [RandomForestClassifier]])
(import [sklearn.metrics [accuracy_score]])

(setv mnist keras.datasets.mnist)
(setv [[train-images train-labels] [test-images test-labels]] (.load_data mnist))

(print f"train-images: {(. train-images shape)}")
(print f"train-labels: {(. train-labels shape)}")
(print f"test-images: {(. test-images shape)}")
(print f"test-labels: {(. test-labels shape)}")

(setv trees (RandomForestClassifier))

(.fit trees (.reshape np train-images [60000, 784]) train-labels)
(print (accuracy_score test-labels
                       (.predict trees (.reshape np test-images [10000, 784]))))