TD_KMeansPredict Function | KMeansPredict | Teradata Vantage - TD_KMeansPredict - Teradata Vantage

Teradata® VantageCloud Lake

Deployment
VantageCloud
Edition
Lake
Product
Teradata Vantage
Published
January 2023
Language
English (United States)
Last Update
2024-04-03
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TD_KMeansPredict uses the k-means algorithm to predict the target class of unseen or new data.

The k-means algorithm calculates the distance between data points to determine the number of groups in a dataset based on the data point clusters.

TD_KMeansPredict function follows this process:

  1. Select the number of clusters (K).
  2. Initialize the centroids.
  3. Assign training data points to clusters based on their proximity to the different clusters
  4. Recalculate centroids.
  5. Repeat the process until the cluster assignments do not change a lot.
  6. Use k-means algorithm to predict the cluster assignments of unseen/test data.