def supervised_leaf_top_down_mpe(node, input_vals, data=None, lls_per_node=None): if len(input_vals) == 0: return None mpe_ids = np.isnan(data[input_vals, node.scope]) mode_data = leaf_predict_mode(node, data[input_vals[mpe_ids], :]) get_mpe_top_down_leaf(node, input_vals, data=data, mode=mode_data[:, 0])
def piecewise_top_down(node, input_vals, lls_per_node, data=None): get_mpe_top_down_leaf(node, input_vals, data=data, mode=piecewise_mode(node))
def param_td_fn(node, input_vals, data=None, lls_per_node=None): get_mpe_top_down_leaf( node, input_vals, data=data, mode=mode_func(node))
def histogram_top_down(node, input_vals, data=None): get_mpe_top_down_leaf(node, input_vals, data=data, mode=histogram_mode(node))