Created
December 15, 2019 21:37
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Classification using K-mean cluster
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| # set number of clusters | |
| kclusters = 4 | |
| sydney_grouped_clustering = sydney_grouped.drop('Suburb', 1) | |
| # run k-means clustering | |
| kmeans = KMeans(n_clusters=kclusters, random_state=0).fit(sydney_grouped_clustering) | |
| # check cluster labels generated for each row in the dataframe | |
| kmeans.labels_[0:10] | |
| sydney_merged.loc[sydney_merged['Cluster Labels'] == 2, sydney_merged.columns[[0] + list(range(4, sydney_merged.shape[1]))]] |
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