clustering.py 文件源码

def cluster_agglomerative(X_train, model_args=None, gridsearch=True, connectivity_graph=True, connectivity_graph_neighbors=10):
    from sklearn.cluster import AgglomerativeClustering
    from sklearn.neighbors import kneighbors_graph
    print('AgglomerativeClustering')

    if connectivity_graph:
        print('Creating k-neighbors graph for connectivity restraint')
        connectivity = kneighbors_graph(X_train, n_neighbors=connectivity_graph_neighbors)
        model_args['connectivity'] = connectivity

    if gridsearch is True:
        ## TODO:
        # add hyperparamter searching. No scoring method available for this model, 
        # so we can't easily use gridsearching.

        raise NotImplementedError('No hyperparameter optimization available yet for this model. Set gridsearch to False')
        # prune(param_grid, model_args)
    else:
        if 'n_clusters' not in model_args:
            raise KeyError('Need to define n_clusters for AgglomerativeClustering')
        param_grid = None

    return ModelWrapper(AgglomerativeClustering, X=X_train, model_args=model_args, param_grid=param_grid, unsupervised=True)