Dimensionality reduction and model training in a database system implementation of a k nearest neighbors model

Abstract

A database system operates by: determining a first query that indicates a first request to generate a K nearest neighbors (KNN) model; executing the first query to generate KNN model data for the KNN model, wherein the KNN model data is set as a reduced dataset for one of a plurality of training iterations; determining a second query that indicates a second request to apply the KNN model to input data; and executing the second query to generate model output of the KNN model for the input data based on, for each row in the input data, identifying a classification label for the each row from the discrete set of labels based on performing the KNN classification algorithm to classify the each row in the input data by applying the reduced data set.