latools/filtering/classifier_obj.py
def fit_kmeans(self, data, n_clusters, **kwargs):
        """
        Fit KMeans clustering algorithm to data.

        Parameters
        ----------
        data : array-like
            A dataset formatted by `classifier.fitting_data`.
        n_clusters : int
            The number of clusters in the data.
        **kwargs
            passed to `sklearn.cluster.KMeans`.

        Returns
        -------
        Fitted `sklearn.cluster.KMeans` object.
        """
        km = cl.KMeans(n_clusters=n_clusters, **kwargs)
        km.fit(data)
        return km
def fit_kmeans(self, data, n_clusters, **kwargs):
        km = cl.KMeans(n_clusters=n_clusters, **kwargs)
        km.fit(data)
        return km
def fit_kmeans ( self , data , n_clusters , * * kwargs ) : km = cl . KMeans ( n_clusters = n_clusters , * * kwargs ) km . fit ( data ) return km
Fit KMeans clustering algorithm to data.

        Parameters
        ----------
        data : array-like
            A dataset formatted by `classifier.fitting_data`.
        n_clusters : int
            The number of clusters in the data.
        **kwargs
            passed to `sklearn.cluster.KMeans`.

        Returns
        -------
        Fitted `sklearn.cluster.KMeans` object.
Fit KMeans clustering algorithm to data .