classification.py 文件源码

def __init__(self, mu=.5, tau=1.0, lamda=1, use_gpu=False, threshold=1e-16,
                 alpha=None, l1_ratio=None, fit_intercept=True,
                 normalize=False, precompute=False, max_iter=10000,
                 copy_X=True, tol=1e-4, warm_start=False, positive=False,
                 random_state=None, selection='cyclic'):
        vs = L1L2(mu=mu, tau=tau, use_gpu=use_gpu, threshold=threshold,
                  alpha=alpha, l1_ratio=l1_ratio, fit_intercept=fit_intercept,
                  normalize=normalize, precompute=precompute,
                  max_iter=max_iter, copy_X=copy_X, tol=tol,
                  warm_start=warm_start, positive=positive,
                  random_state=random_state, selection=selection)
        mdl = RidgeClassifier(
            alpha=lamda, fit_intercept=fit_intercept,
            normalize=normalize, copy_X=copy_X, max_iter=max_iter,
            tol=tol, random_state=random_state)
        super(L1L2TwoStepClassifier, self).__init__(
            (('l1l2', vs), ('ridge', mdl)))

        self.mu = mu
        self.tau = tau
        self.lamda = lamda
        self.alpha = alpha
        self.l1_ratio = l1_ratio
        self.use_gpu = use_gpu
        self.threshold = threshold

        self.fit_intercept = fit_intercept
        self.normalize = normalize
        self.precompute = precompute
        self.max_iter = max_iter
        self.copy_X = copy_X
        self.tol = tol
        self.warm_start = warm_start
        self.positive = positive
        self.intercept_ = 0.0
        self.random_state = random_state
        self.selection = selection