import cyanure as ars #load ckn_mnist dataset 10 classes, n=60000, p=2304 data=np.load('ckn_mnist.npz'); y=data['y']; X=data['X'] #center and normalize the rows of X in-place, without performing any copy ars.preprocess(X,centering=True,normalize=True,columns=False) #declare a multinomial logistic classifier with group Lasso regularization classifier=ars.MultiClassifier(loss='logistic',penalty='l2') # uses the auto solver by default, performs at most 500 epochs classifier.fit(X,y,lambd=0.01/X.shape[0],nepochs=500,tol=1e-3)