decompose.py 文件源码

def fc_kernel(X, Y, copy_X=True, W=None, B=None, ret_reg=False,fit_intercept=True):
    """
    return: n c
    """
    assert copy_X == True
    assert len(X.shape) == 2
    if dcfgs.ls == cfgs.solvers.gd:
        w = Worker()
        def wo():
            from .GDsolver import fc_GD
            a,b=fc_GD(X,Y, W, B, n_iters=1)
            return {'a':a, 'b':b}
        outputs = w.do(wo)
        return outputs['a'], outputs['b']
    elif dcfgs.ls == cfgs.solvers.tls:
        return tls(X,Y, debug=True)
    elif dcfgs.ls == cfgs.solvers.keras:
        _reg=keras_kernel()
        _reg.fit(X, Y, W, B)
        return _reg.coef_, _reg.intercept_
    elif dcfgs.ls == cfgs.solvers.lightning:
        #_reg = SGDRegressor(eta0=1e-8, intercept_decay=0, alpha=0, verbose=2)
        _reg = CDRegressor(n_jobs=-1,alpha=0, verbose=2)
        if 0:
            _reg.intercept_=B
            _reg.coef_=W
    elif dcfgs.fc_ridge > 0:
        _reg = Ridge(alpha=dcfgs.fc_ridge)
    else:
        _reg = LinearRegression(n_jobs=-1 , copy_X=copy_X, fit_intercept=fit_intercept)
    _reg.fit(X, Y)
    if ret_reg:
        return _reg
    return _reg.coef_, _reg.intercept_