This book covers the techniques of data mining, knowledge discovery, genetic algorithms, neural networks, bootstrapping, machine learning, and Monte Carlo simulation. Computational finance, an excit
Although Inductive Logic Programming (ILP) is generally thought of as a research area at the intersection of machine learning and computational logic, Bergadano and Gunetti propose that most of the re
A concise, rigorous, yet accessible, account of the fundamentals of constrained optimization theory. Many problems arising in diverse fields such as machine learning, medicine, chemical engineering, s
The third edition of a bestseller, Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data is still the only book, to date, to distinguish betw
The Support Vector Machine is a powerful new learning algorithm for solving a variety of learning and function estimation problems, such as pattern recognition, regression estimation, and operator inv
Genetic algorithms are playing an increasingly important role in studies of complex adaptive systems, ranging from adaptive agents in economic theory to the use of machine learning techniques in the d
In this thought-provoking study of work, worker, and machine in the postindustrial age, Hirschhorn points out that factories will become places of learning where the worker must be able to diagnose an
