kgrid_r0.py 文件源码

def gs_Lasso_norm( xM, yV, alphas_log = (-1, 1, 9)):

    print(xM.shape, yV.shape)

    clf = linear_model.Lasso( normalize = True)
    #parmas = {'alpha': np.logspace(1, -1, 9)}
    parmas = {'alpha': np.logspace( *alphas_log)}
    kf5_c = model_selection.KFold( n_splits = 5, shuffle=True)
    #kf5 = kf5_c.split( xM)
    gs = model_selection.GridSearchCV( clf, parmas, scoring = 'r2', cv = kf5_c, n_jobs = -1)

    gs.fit( xM, yV)

    return gs