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What is Implicative Assertions

Handbook of Research on Innovations in Database Technologies and Applications: Current and Future Trends
Implications describe the regularities mutually connecting objects, properties and classes of objects. They can be given explicitly by an expert or derived automatically from examples via some learning process.
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
More Results
Classification Reasoning as a Basic Part of Machine Learning
Implicative assertions describe regular relationships between objects, their properties, classes of objects, and between properties of different objects. They are represented in the “if-then” form and can be given explicitly by an expert or derived automatically from examples with the help of a learning process.
Full Text Chapter Download: US $37.50 Add to Cart
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