Prediction of Recursive Real-Valued Functions from Finite Examples

Learning figures with the Hausdorff metric by fractals—towards computable binary classification

“…However, analysis of learning for continuous objects, such as classification, regression, and clustering for multivariate data, with Gold's model is still under development, despite such settings being typical in modern machine learning. To the best of our knowledge, the only line of studies devoted to learning of real-valued functions was by Arikawa (1997, 2001) Apsītis et al (1999), Hirowatari et al (2003Hirowatari et al ( , 2005Hirowatari et al ( , 2006, where they addressed the analysis of learnable classes of real-valued functions using computable representations of real numbers. 2 We therefore need a new theoretical and computational framework for modern machine learning based on Gold's learning model with discretization of numerical data.…”