The Large-Scale Structure of Inductive Inference investigates the relations of inductive support on the large scale, among the totality of facts comprising a science or science in general. These relations form a massively entangled, non-hierarchical structure which is discovered by provisional hypotheses that are later supported by other facts drawn from the entirety of the science. What results is a benignly circular, self-supporting inductive structure in which universal rules are not employed, the classical Humean problem cannot be formulated and analogous regress arguments fail.
Building upon and furthering The Material Theory of Induction, this book presents general claims and arguments for the large-scale relations of inductive support according to the material theory of induction, in which inductive inferences are not warranted by universal rules but by facts particular to each context. It begins with a thorough discussion of general claims and arguments for the large-scale structure of inductive relations, followed by case studies in the history of science that support, and further illustrate, those claims.
With The Large-Scale Structure of Inductive Inference, author John D. Norton presents a novel, thoroughly researched, and sustained remedy to the enduring failures of formal approaches of inductive inference.
The Large-Scale Structure of Inductive Inference investigates the relations of inductive support on the large scale, among the totality of facts comprising a science or science in general. These relations form a massively entangled, non-hierarchical structure which is discovered by provisional hypotheses that are later supported by other facts drawn from the entirety of the science. What results is a benignly circular, self-supporting inductive structure in which universal rules are not employed, the classical Humean problem cannot be formulated and analogous regress arguments fail.
Building upon and furthering The Material Theory of Induction, this book presents general claims and arguments for the large-scale relations of inductive support according to the material theory of induction, in which inductive inferences are not warranted by universal rules but by facts particular to each context. It begins with a thorough discussion of general claims and arguments for the large-scale structure of inductive relations, followed by case studies in the history of science that support, and further illustrate, those claims.
With The Large-Scale Structure of Inductive Inference, author John D. Norton presents a novel, thoroughly researched, and sustained remedy to the enduring failures of formal approaches of inductive inference.
Fundamentals.- Background on Text Classification.- Kernel Machines for Text Classification.- Approaches and techniques.- Enhancing SVMs for Text Classification.- Scaling RVMs for Text Classification...
In this classic work of philosophy, Thilly provides a comprehensive overview of inductive reasoning and its role in scientific inquiry. With clear examples and lucid prose, Thilly's text remains an...
Ten years ago in August 1977 Malcom Longair and Jan Einasto organized IAU Symposium nO 79 on exactly the same exciting and most important topic i.e. the Large Scale Structure of the Universe. Many of...
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