20 Result(s)
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Chapter and Conference Paper
The Use of Compound Attributes inAQ Learning
Compound attributes are named groups of attributes that have been introduced in Attributional Calculus (AC) to facilitate learning descriptions of objects whose components are characterized by different subset...
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Chapter and Conference Paper
Learning Symbolic User Models for Intrusion Detection: A Method and Initial Results
This paper briefly describes the LUS-MT method for automatically learning user signatures (models of computer users) from datastreams capturing users’ interactions with computers. The signatures are in the for...
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Chapter and Conference Paper
A Rules-to-Trees Conversion in the Inductive Database System VINLEN
Decision trees and rules are completing methods of knowledge representation. Both have advantages in some applications. Algorithms that convert trees to rules are common. In the paper an algorithm that convert...
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Chapter and Conference Paper
Knowledge Visualization Using Optimized General Logic Diagrams
Knowledge Visualizer (KV) uses a General Logic Diagram (GLD) to display examples and/or various forms of knowledge learned from them in a planar model of a multi-dimensional discrete space. Knowledge can be in...
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Article
Introduction
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Chapter and Conference Paper
The Development of the Inductive Database System VINLEN: A Review of Current Research
Current research on the VINLEN inductive database system is briefly reviewed and illustrated by selected results. The goal of research on VINLEN is to develop a methodology for deeply integrating a wide range of
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Article
Selecting Examples for Partial Memory Learning
This paper describes a method for selecting training examples for a partial memory learning system. The method selects extreme examples that lie at the boundaries of concept descriptions and uses these example...
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Article
LEARNABLE EVOLUTION MODEL: Evolutionary Processes Guided by Machine Learning
A new class of evolutionary computation processes is presented, called Learnable Evolution Model or LEM. In contrast to Darwinian-type evolution that relies on mutation, recombination, and selection operators,...
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Article
Guest Editors' Introduction
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Article
An Integration of Rule Induction and Exemplar-Based Learning for Graded Concepts
This paper presents a method for learning graded concepts. Our method uses a hybrid concept representation that integrates numeric weights and thresholds with rules and combines rules with exemplars. Concepts are...
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Article
An integration of rule induction and exemplar-based learning for graded concepts
This paper presents a method for learninggraded concepts. Our method uses a hybrid concept representation that integrates numeric weights and thresholds with rules and combines rules with exemplars. Concepts are ...
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Article
Hypothesis-Driven Constructive Induction in AQ17-HCI: A Method and Experiments
The proposed method for constructive induction searches for concept descriptions in a representation space that is being iteratively improved. In each iteration, the system learns concept description from trai...
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Article
Introduction
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Article
Introduction
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Article
Inferential theory of learning as a conceptual basis for multistrategy learning
In view of a great proliferation of machine learning methods and paradigms, there is a need for a general conceptual framework that would explain their interrelationships and provide a basis for their integrat...
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Article
Inferential Theory of Learning as a Conceptual Basis for Multistrategy Learning
In view of a great proliferation of machine learning methods and paradigms, there is a need for a general conceptual framework that would explain their interrelationships and provide a basis for their integrat...
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Article
Editorial: Machine Learning and Discovery
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Article
Editorial: Machine learning and discovery
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Article
Integrating quantitative and qualitative discovery: The ABACUS system
Most research on inductive learning has been concerned with qualitative learning that induces conceptual, logic-style descriptions from the given facts. In contrast, quantitative learning deals with discoverin...
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Article
Integrating Quantitative and Qualitative Discovery: The ABACUS System
Most research on inductive learning has been concerned with qualitative learning that induces conceptual, logic-style descriptions from the given facts. In contrast, quantitative learning deals with discoverin...
