Beispiel #1
0
    def __init__(self, parameters):

        self.params = parameters

        # make sure nobody accidentally added new parameters (by e.g. spelling mistakes)
        assert len(parameters) == len(utils_parameters.get_parameter_dict())

        # get the input domain on which the utility is defined
        self.input_domain = self.initialise_input_domain()

        # get a user with preferences over the input domain
        self.user = self.initialise_user()

        # get an acquirer which will pick the queries
        self.acquirer = self.initialise_acquirer()

        # initialise the Gaussian process
        self.gp = self.initialise_gaussian_process()

        # initialise dataset
        self.dataset = self.initialise_dataset()

        self.curr_x_max = None
        self.curr_x_new = None

        self.visualiser = self.initialise_visualiser()
for prior_type, ref_min, ref_max in [['zero', False, False],
                                     ['linear-zero', 'full', 'full']]:

    for utl_noise in [0.01, 0.1]:

        plt.subplot(2, 2, plt_idx)

        # loop through query types
        for query_type in [
                'pairwise', 'clustering', 'ranking', 'clustering4', 'top_rank'
        ]:

            # get the  parameters
            params = utils_parameters.get_parameter_dict(
                num_objectives=num_obj,
                query_type=query_type,
                utility_noise=utl_noise)

            params['num queries'] = num_queries

            params['gp prior mean'] = prior_type
            params['reference min'] = ref_min
            params['reference max'] = ref_max

            if params['query type'] == 'clustering4':
                params['query type'] = 'clustering'
                params['num clusters'] = 4

            params['seed'] = start_seed

            utilities = np.zeros((num_iter, params['num queries']))
Beispiel #3
0
            for virtcomps in [
                    'none', 'VC grid', 'VC pcs', 'VC grid begin',
                    'VC pcs begin'
            ]:

                # 5 is the number of diff query types;
                # 50 is the number of queries we ask
                utl_vals = np.zeros((5 * num_iter, 50))
                iter_idx = 0

                for query_type in [
                        'pairwise', 'clustering', 'ranking', 'top_rank'
                ]:

                    params = utils_parameters.get_parameter_dict(
                        query_type=query_type,
                        num_objectives=num_obj,
                        utility_noise=noise_level)
                    if virtcomps == 'VC grid':
                        params['VC grid'] = True
                    elif virtcomps == 'VC pcs begin':
                        params['VC grid begin'] = True

                    elif virtcomps == 'VC pcs':
                        params['VC pcs'] = True
                    elif virtcomps == 'VC pcs begin':
                        params['VC pcs begin'] = True

                    plt.title(query_type)

                    params['seed'] = start_seed