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What is Inductive Transitions

Handbook of Research on Innovations in Database Technologies and Applications: Current and Future Trends
These are the processes of extending or narrowing collections of values (objects). They can be smooth and boundary. Upon smooth transition, a certain assigned property of the generated collections does not change. Upon boundary transition, a certain assigned property of the generated collections changes to the opposite one.
Published in Chapter:
Machine Learning as a Commonsense Reasoning Process
Xenia Naidenova (Military Medical Academy, Russia)
DOI: 10.4018/978-1-60566-242-8.ch065
Abstract
One of the most important tasks in database technology is to combine the following activities: data mining or inferring knowledge from data and query processing or reasoning on acquired knowledge. The solution of this task requires a logical language with unified syntax and semantics for integrating deductive (using knowledge) and inductive (acquiring knowledge) reasoning. In this paper, we propose a unified model of commonsense reasoning. We also demonstrate that a large class of inductive machine learning (ML) algorithms can be transformed into the commonsense reasoning processes based on wellknown deduction and induction logical rules. The concept of a good classification (diagnostic) test (Naidenova & Polegaeva, 1986) is the basis of our approach to combining deductive and inductive reasoning.
Full Text Chapter Download: US $37.50 Add to Cart
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Classification Reasoning as a Basic Part of Machine Learning
These are the processes of extending or narrowing sets of values (objects). They can be smooth and boundary. Upon smooth transition, a certain assigned property of the generated sets does not change. Upon boundary transition, a certain assigned property of the generated sets changes to the opposite one.
Full Text Chapter Download: US $37.50 Add to Cart
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