_jgrid_r0.py 文件源码

def gs_Ridge_BIKE( A_list, yV, XX = None, alphas_log = (1, -1, 9), n_folds = 5, n_jobs = -1):
    """
    As is a list of A matrices where A is similarity matrix. 
    X is a concatened linear descriptors. 
    If no X is used, X can be empty
    """

    clf = binary_model.BIKE_Ridge( A_list, XX)
    parmas = {'alpha': np.logspace( *alphas_log)}
    ln = A_list[0].shape[0] # ls is the number of molecules.

    kf_n = cross_validation.KFold( ln, n_folds=n_folds, shuffle=True)
    gs = grid_search.GridSearchCV( clf, parmas, scoring = 'r2', cv = kf_n, n_jobs = n_jobs)

    AX_idx = np.array([list(range( ln))]).T
    gs.fit( AX_idx, yV)

    return gs