Inference Vs Induction
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Aristotle's Induction and the Inference of First Principles
Author: David Botting
language: en
Publisher: Rowman & Littlefield
Release Date: 2024-10-15
Aristotle's Induction and the Inference of First Principles observes that Aristotle’s reputation as an empiricist has come under threat. In the Posterior Analytics, Aristotle puts forward a foundationalist theory of scientific knowledge that problematizes knowing the science's first principles empirically. Aristotle states that we know the principles through induction but also that induction is inadequate for knowing essences. In response to this tension, rationalists claim that Aristotle equivocates between two conceptions of induction, enumerative and intuitive:"intuitive induction" being that which grasps the principles and provides direct knowledge of essences, “enumerative induction” being that which is said to be inadequate. Empiricists preserve an empiricist road to first principles by downplaying enumerative induction’s role. In order to preserve Aristotle's avowals that it is by induction that we know the principles while avoiding the rationalist alternative, David Botting provides an inferentialist account of induction, showing how the content of a first principle is inferentially known but not its necessity, which must be proved by constructing the first principle from simpler elements. A world governed by natural necessities and not just brute regularities is knowable through the senses and without resorting to super-empirical acts or faculties of intuition.
Statistical and Inductive Inference by Minimum Message Length
Author: C.S. Wallace
language: en
Publisher: Springer Science & Business Media
Release Date: 2005-05-26
The Minimum Message Length (MML) Principle is an information-theoretic approach to induction, hypothesis testing, model selection, and statistical inference. MML, which provides a formal specification for the implementation of Occam's Razor, asserts that the ‘best’ explanation of observed data is the shortest. Further, an explanation is acceptable (i.e. the induction is justified) only if the explanation is shorter than the original data. This book gives a sound introduction to the Minimum Message Length Principle and its applications, provides the theoretical arguments for the adoption of the principle, and shows the development of certain approximations that assist its practical application. MML appears also to provide both a normative and a descriptive basis for inductive reasoning generally, and scientific induction in particular. The book describes this basis and aims to show its relevance to the Philosophy of Science. Statistical and Inductive Inference by Minimum Message Length will be of special interest to graduate students and researchers in Machine Learning and Data Mining, scientists and analysts in various disciplines wishing to make use of computer techniques for hypothesis discovery, statisticians and econometricians interested in the underlying theory of their discipline, and persons interested in the Philosophy of Science. The book could also be used in a graduate-level course in Machine Learning and Estimation and Model-selection, Econometrics and Data Mining. C.S. Wallace was appointed Foundation Chair of Computer Science at Monash University in 1968, at the age of 35, where he worked until his death in 2004. He received an ACM Fellowship in 1995, and was appointed Professor Emeritus in 1996. Professor Wallace made numerous significant contributions to diverse areas of Computer Science, such as Computer Architecture, Simulation and Machine Learning. His final research focused primarily on the Minimum Message Length Principle.
Inductive Probability
First published in 1961, Inductive Probability is a dialectical analysis of probability as it occurs in inductions. The book elucidates on the various forms of inductive, the criteria for their validity, and the consequent probabilities. This survey is complemented with a critical evaluation of various arguments concerning induction and a consideration of relation between inductive reasoning and logic. The book promises accessibility to even casual readers of philosophy, but it will hold particular interest for students of Philosophy, Mathematics and Logic.