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assign()
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Assigns data points to k clusters |
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avg_sil_score()
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avg_sil_score
This function takes in a vector of cluster labels and a corresponding array of points and calculates the average silhouette score across all clusters.
It returns the value of the average silhouette score. |
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calc_centers()
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Calculates center coordinates of each cluster |
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find_elbow()
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find_elbow
This function takes in unlabeled, scaled data and performs clustering using the KMeans clustering algorithm values of K up to the min(10, n_samples - 1).
It returns the value for K which maximizes the mean silhouette scores across all clusters. |
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fit()
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Finds k clusters in data points. |
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fit_assign()
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Finds k clusters in data points and assigns each point to a cluster. |
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init_centers()
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Chooses initial cluster locations using Kmeans++ |
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measure_dist()
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Measures distance from data points to cluster centers |
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preprocess()
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This function takes in training data and applies some preprocessing steps
such as scaling and imputation |
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show_clusters()
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This function reduces a data set to 2 dimensions using principle component
analysis (PCA) and colours clusters of points. |