Missing labels_ and predict function for K-Means

[liufsd]

Great work. but k-means missing labels_ and predict function like sklearn ~ https://scikit-learn.org/stable/modules/generated/sklearn.cluster.KMeans.html#sklearn.cluster.KMeans

[liufsd]

     Examples
    --------
    >>> from sklearn.cluster import KMeans
    >>> import numpy as np
    >>> X = np.array([[1, 2], [1, 4], [1, 0],
    ...               [10, 2], [10, 4], [10, 0]])
    >>> kmeans = KMeans(n_clusters=2, random_state=0).fit(X)
    >>> kmeans.labels_
    array([1, 1, 1, 0, 0, 0], dtype=int32)
    >>> kmeans.predict([[0, 0], [12, 3]])
    array([1, 0], dtype=int32)
    >>> kmeans.cluster_centers_
    array([[10.,  2.],
           [ 1.,  2.]])

https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/cluster/k_means_.py

[annoviko]

Hello, @liufsd,
Thank you for your comments. About labels: pyclustering provides labels in different way, see get_clusters() method - https://pyclustering.github.io/docs/0.9.0/html/da/d22/classpyclustering_1_1cluster_1_1kmeans_1_1kmeans.html .

About prediction - I agree, it is useful feature, I will introduce this method.

[liufsd]

thanks～

[liufsd]

Hello , any progress ？

[annoviko]

Hello, @liufsd ,
Don't worry, it will be delivered in 0.9.1.

[liufsd]

ok~

[vivekverma080698]

Hi @annoviko how can I contribute to this predict feature ?.
I need this feature in great hurry for OPTICS. Thank you

[annoviko]

Hello, @vivekverma080698 , at least article is required that described how to do that for OPTICS. And implementation itself is also can be contributed. In this thread we were talking about prediction for K-Means.

[liufsd]

@annoviko Hello , any progress ？? ？
😢