# BisectingKMeansSummary¶

class pyspark.ml.clustering.BisectingKMeansSummary(java_obj=None)[source]

Bisecting KMeans clustering results for a given model.

New in version 2.1.0.

Attributes

 cluster DataFrame of predicted cluster centers for each training data point. clusterSizes Size of (number of data points in) each cluster. featuresCol Name for column of features in predictions. k The number of clusters the model was trained with. numIter Number of iterations. predictionCol Name for column of predicted clusters in predictions. predictions DataFrame produced by the model’s transform method. trainingCost Sum of squared distances to the nearest centroid for all points in the training dataset.

Attributes Documentation

cluster

DataFrame of predicted cluster centers for each training data point.

New in version 2.1.0.

clusterSizes

Size of (number of data points in) each cluster.

New in version 2.1.0.

featuresCol

Name for column of features in predictions.

New in version 2.1.0.

k

The number of clusters the model was trained with.

New in version 2.1.0.

numIter

Number of iterations.

New in version 2.4.0.

predictionCol

Name for column of predicted clusters in predictions.

New in version 2.1.0.

predictions

DataFrame produced by the model’s transform method.

New in version 2.1.0.

trainingCost

Sum of squared distances to the nearest centroid for all points in the training dataset. This is equivalent to sklearn’s inertia.

New in version 3.0.0.