KMeans¶
K-means clustering with support for k-means|| initialization proposed by Bahmani et al
Input¶
It takes in a DataFrame as input and performs K-Means clustering
Output¶
The input DataFrame is passed along to the next Processors
Type¶
ml-estimator
Class¶
fire.nodes.ml.NodeKMeans
Fields¶
| Name | Title | Description |
|---|---|---|
| featuresCol | Features Column | Features column of type vectorUDT for model fitting. |
| k | K | The number of clusters to create. |
| maxIter | Max Iterations | The maximum number of iterations. |
| predictionCol | Prediction Column | The prediction column created during model scoring. |
| seed | Seed | Random Seed. |
| tol | Tolerence | The convergence tolerance for iterative algorithms. |
| initMode | initMode | The initialization algorithm mode. |
| initSteps | initSteps | The number of steps for the k-means|| initialization mode. It will be ignored when other initialization modes are chosen. |
Details¶
K-means clustering with support for k-means|| initialization proposed by Bahmani et al
More at Spark MLlib/ML docs page : http://spark.apache.org/docs/latest/mllib-clustering.html#k-means