kmeans.py 文件源码

def kmeans_aic(model, X, **kwargs):
    '''AIC (Akaike Information Criterion) for k-means for model selection

    Parameters:
        :model:  An elm.pipeline.Pipeline with KMeans or MiniBatchKMeans as final step in Pipeline
        :X:      The X data that were just given to "fit", or "partial_fit"
        :kwargs: placeholder - ignored

    Returns:
        :AIC: float

    '''

    k, m = model._estimator.cluster_centers_.shape
    if isinstance(X, xr.DataArray):
        n = X.flat.values.shape[0]
    else:
        n = X.shape[0]
    d = model._estimator.inertia_
    aic =  d + 2 * m * k
    delattr(model._estimator, 'labels_')
    return aic