Python optimize_maximum_likelihood示例

示例#1

    def calc_error(truth_dict):
        X = truth_dict['data']
        Y = truth_dict['labels']

        expected = truth_dict['prior_mean']
        predicted = optimize_maximum_likelihood(X, Y)[0]

        error = calc_mean_squared_error(expected, predicted, as_log=True)

        return error

示例#2

文件： test_model_integration.py 项目： starflettw/plda

def expected_parameters(data_dict):
    X = data_dict['data']
    Y = data_dict['labels']

    params = optimize_maximum_likelihood(X, Y)

    params_dict = dict()
    params_dict['m'] = params[0]
    params_dict['A'] = params[1]
    params_dict['Psi'] = params[2]
    params_dict['relevant_U_dims'] = params[3]
    params_dict['inv_A'] = params[4]

    return params_dict

示例#3

def fitted_parameters(truth_dict):
    X = truth_dict['data']
    Y = truth_dict['labels']

    return optimize_maximum_likelihood(X, Y)