Building Bridges between Regression, Clustering, and Classification

Lawrence Stewart; Francis Bach; Quentin Berthet

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arXiv · 2502.02996

Building Bridges between Regression, Clustering, and Classification

Lawrence Stewart·Francis Bach·Quentin Berthet

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Abstract

Regression, the task of predicting a continuous scalar target y based on some features x is one of the most fundamental tasks in machine learning and statistics. It has been observed and theoretically analyzed that the classical approach, meansquared error minimization, can lead to suboptimal results when training neural networks. In this work, we propose a new method to improve the training of these models on regression tasks, with continuous scalar targets. Our method is based on casting this task in a different fashion, using a target encoder, and a prediction decoder, inspired by approaches in classification and clustering. We showcase the performance of our method on a wide range of real-world datasets.

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Lawrence Stewart, Francis Bach, Quentin Berthet. 2025-02-05. Building Bridges between Regression, Clustering, and Classification. https://arxiv.org/abs/2502.02996

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