Knowledge Discovery using Unsupervised Cognition

• URL: http://arxiv.org/abs/2409.20064v1
• Date: Mon, 30 Sep 2024 08:07:29 GMT
• Title: Knowledge Discovery using Unsupervised Cognition
• Authors: Alfredo Ibias, Hector Antona, Guillem Ramirez-Miranda, Enric Guinovart,
• Abstract summary: Unsupervised Cognition is a novel unsupervised learning algorithm that focus on modelling the learned data. This paper presents three techniques to perform knowledge discovery over an already trained Unsupervised Cognition model.
• Score: 2.6563873893593826
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Knowledge discovery is key to understand and interpret a dataset, as well as to find the underlying relationships between its components. Unsupervised Cognition is a novel unsupervised learning algorithm that focus on modelling the learned data. This paper presents three techniques to perform knowledge discovery over an already trained Unsupervised Cognition model. Specifically, we present a technique for pattern mining, a technique for feature selection based on the previous pattern mining technique, and a technique for dimensionality reduction based on the previous feature selection technique. The final goal is to distinguish between relevant and irrelevant features and use them to build a model from which to extract meaningful patterns. We evaluated our proposals with empirical experiments and found that they overcome the state-of-the-art in knowledge discovery.

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