clustering.py 文件源码

def cluster_birch(X_train, model_args=None, gridsearch=True):
    from sklearn.cluster import Birch
    print('Birch')

    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 Birch')
        param_grid = None

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