Evolutionary Applications for Financial Prediction: Classification Methods to Gather Patterns Using Genetic Programming - Couverture souple

Garcia Almanza, Dr. Alma Lilia; Edward Tsang, Professor

 
9783639307672: Evolutionary Applications for Financial Prediction: Classification Methods to Gather Patterns Using Genetic Programming
Couverture souple
ISBN 10 : 3639307674 ISBN 13 : 9783639307672
Editeur : VDM Verlag Dr. Müller, 2011

Synopsis

This book presents three applications, based on Machine Learning and Genetic Programming, which are devoted to find useful patterns to predict future events. The objective is to train the algorithms by using past data to produce a classifier that identifies the positive cases and discriminates the false alarms. This work uses examples for predicting future opportunities in financial stock markets in cases where the number of profitable opportunities is scarce. However, when the number of positive examples is small in comparison with the number of total cases, the identification of useful patterns becomes a serious challenge. Nevertheless, the objective of many real world problems, is precisely to identify the minority class as the fraud detection problem, or medical diagnosis and many other examples. The techniques of this book are suitable to deal with imbalanced data sets, provide comprehensible results that allow users to understand the factors that are involved in the decision, as well as to generate a range of solutions that let the user choose the best trade off according to their risk preferences.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

This book presents three applications, based on Machine Learning and Genetic Programming, which are devoted to find useful patterns to predict future events. The objective is to train the algorithms by using past data to produce a classifier that identifies the positive cases and discriminates the false alarms. This work uses examples for predicting future opportunities in financial stock markets in cases where the number of profitable opportunities is scarce. However, when the number of positive examples is small in comparison with the number of total cases, the identification of useful patterns becomes a serious challenge. Nevertheless, the objective of many real world problems, is precisely to identify the minority class as the fraud detection problem, or medical diagnosis and many other examples. The techniques of this book are suitable to deal with imbalanced data sets, provide comprehensible results that allow users to understand the factors that are involved in the decision, as well as to generate a range of solutions that let the user choose the best trade off according to their risk preferences.

Biographie de l'auteur

Dr. Alma Lilia García-Almanza is PhD in Computer Science from the University of Essex, her research interests are on evolutionary computation, machine learning, data mining and financial forecasting. Professor Edward Tsang is the co-founder and Director of the Centre for Computational Finance and Economic Agents at University of Essex.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
VDM Verlag Dr. Müller
Date d'édition
2011
Langue
anglais
ISBN 10 
3639307674
ISBN 13 
9783639307672
Reliure
Broché
Nombre de pages
172
Coordonnées du fabricant
non disponible
Personne responsable
non disponible