Learning based on neurovectors for tabular data: a new neural network approach

2025/06/08 by J. C. Husillos, Andres Gallego, Husillos, J. C. +5
Computer Science · #Advanced Neural Network Applications #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Data Classification

paper · pdf · doi:10.48550/arxiv.2506.07185

openalex publication_date 2025/06/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In this paper, we present a novel learning approach based on Neurovectors, an innovative paradigm that structures information through interconnected nodes and vector relationships for tabular data processing. Unlike traditional artificial neural networks that rely on weight adjustment through backpropagation, Neurovectors encode information by structuring data in vector spaces where energy propagation, rather than traditional weight updates, drives the learning process, enabling a more adaptable and explainable learning process. Our method generates dynamic representations of knowledge through neurovectors, thereby improving both the interpretability and efficiency of the predictive model. Experimental results using datasets from well-established repositories such as the UCI machine learning repository and Kaggle are reported both for classification and regression. To evaluate its performance, we compare our approach with standard machine learning and deep learning models, showing that Neurovectors achieve competitive accuracy.

Citations

• Revisiting Nearest Neighbor for Tabular Data: A Deep Tabular Baseline Two Decades Later
• NCART: Neural Classification and Regression Tree for Tabular Data
• Language Models are Realistic Tabular Data Generators
• TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second
• DANets: Deep Abstract Networks for Tabular Data Classification and Regression
• Revisiting Deep Learning Models for Tabular Data
• Tabular Data: Deep Learning is Not All You Need
• TabTransformer: Tabular Data Modeling Using Contextual Embeddings
• Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data

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• TabKAN: Advancing Tabular Data Analysis using Kolmogorov-Arnold Network
• Simple Modifications to Improve Tabular Neural Networks