Recipe: How to do Agglomerative Clustering in Python?
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How to do Agglomerative Clustering in Python?

This recipe helps you do Agglomerative Clustering in Python
In [2]:
## How to do Agglomerative Clustering in Python
def Snippet_156():
    print()
    print(format('How to do Agglomerative Clustering in Python','*^82'))

    import warnings
    warnings.filterwarnings("ignore")

    # load libraries
    from sklearn import datasets
    from sklearn.preprocessing import StandardScaler
    from sklearn.cluster import AgglomerativeClustering
    import pandas as pd
    import seaborn as sns
    import matplotlib.pyplot as plt

    # Load data
    iris = datasets.load_iris()
    X = iris.data; data = pd.DataFrame(X)
    cor = data.corr()
    sns.heatmap(cor, square = True); plt.show()

    # Standarize features
    scaler = StandardScaler()
    X_std = scaler.fit_transform(X)
    # Conduct Agglomerative Clustering
    clt = AgglomerativeClustering(linkage='complete',
                affinity='euclidean', n_clusters=5)

    # Train model
    model = clt.fit(X_std)

    # Predict clusters
    clusters = pd.DataFrame(model.fit_predict(X_std))
    data['Cluster'] = clusters

    # Visualise cluster membership
    fig = plt.figure(); ax = fig.add_subplot(111)
    scatter = ax.scatter(data[0],data[1], c=data['Cluster'],s=50)
    ax.set_title('Agglomerative Clustering')
    ax.set_xlabel('X0'); ax.set_ylabel('X1')
    plt.colorbar(scatter); plt.show()

Snippet_156()
*******************How to do Agglomerative Clustering in Python*******************


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