

def gplvm_oil_100(optimize=True, verbose=1, plot=True):
    import GPy
    import pods
    data = pods.datasets.oil_100()
    Y = data['X']
    kernel = (GPy.kern.RBF(6, ARD=True) + GPy.kern.Bias(6))
    m = GPy.models.GPLVM(optimize, 6, kernel=kernel)
    m.data_labels = data['Y'].argmax(axis=1)
    if optimize:
        m.optimize('scg', messages=verbose)
    if plot:
        m.plot_latent(labels=m.data_labels)
    return m

dataset/ETHPy150Open SheffieldML/GPy/GPy/examples/dimensionality_reduction.py gplvm_oil_100/VarMisuse@77/99 `Y`->`optimize`