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Self-organising fuzzy logic classifier
TLDR
We present a self-organising nonparametric fuzzy rule-based classifier, which is able to address a wide variety of problems with specific needs. Expand
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Empirical Data Analytics
TLDR
In this paper, we propose an approach to data analysis that is based entirely on the empirical observations of discrete data samples and the relative proximity of these points in the data space. Expand
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A Generalized Methodology for Data Analysis
TLDR
In this paper, we propose a functional approach to estimate data ensemble properties, which is based entirely on the empirical observations of discrete data samples and the relative proximity of these points in the data space. Expand
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Autonomous Learning Multimodel Systems From Data Streams
TLDR
In this paper, an approach to autonomous learning of a multimodel system from streaming data, named ALMMo, is proposed. Expand
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Empirical data analysis: A new tool for data analytics
TLDR
In this paper, a novel empirical data analysis approach (abbreviated as EDA) is introduced which is entirely data-driven and free from restricting assumptions and pre-defined problem- or user-specific parameters and thresholds. Expand
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Empirical Approach to Machine Learning
TLDR
This book provides a ‘one-stop source’ for all readers who are interested in a new, empirical approach to machine learning that, unlike traditional methods, successfully addresses the demands of today’s data-driven world. Expand
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Stability of Evolving Fuzzy Systems Based on Data Clouds
TLDR
We introduce the stability proof of a class of EFSs based on data clouds, which are grounded at the AnYa type fuzzy systems and the recently introduced empirical data analytics methodological framework. Expand
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A method for autonomous data partitioning
TLDR
We propose a fully autonomous, non-parametric, data partitioning algorithm, which is able to automatically recognize local maxima of the density from empirical observations and use them as the focal points to form shape-free data clouds, i.e. a form of Voronoi tessellation. Expand
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Self-Organised direction aware data partitioning algorithm
TLDR
In this paper, a novel fully data driven algorithm, named Self-Organised Direction Aware (SODA) data partitioning and forming data clouds is proposed. Expand
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Autonomous Data Density based clustering method
TLDR
We propose a new clustering approach which is fully autonomous, in the sense that it does not require parameters to be pre-defined. Expand
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