INNER CODE UNIT · Python

clustering

burkesquires/python_biologist · 06_data_vis_python/bokeh/server/app/clustering/main.py:26

def clustering(X, algorithm, n_clusters):
    # normalize dataset for easier parameter selection
    X = StandardScaler().fit_transform(X)

    # estimate bandwidth for mean shift
    bandwidth = cluster.estimate_bandwidth(X, quantile=0.3)

    # connectivity matrix for structured Ward
    connectivity = kneighbors_graph(X, n_neighbors=10, include_self=False)

    # make connectivity symmetric
    connectivity = 0.5 * (connectivity + connectivity.T)

    # Generate the new colors:
    if algorithm=='MiniBatchKMeans':
        model = cluster.MiniBatchKMeans(n_clusters=n_clusters, n_init=3)

    elif algorithm=='Birch':

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