Grammar-Based Feature Generation for Time-Series Prediction, 2015 SpringerBriefs in Computational Intelligence Series
Auteurs : De Silva Anthony Mihirana, Leong Philip H. W.
Introduction.- Feature Selection.- Grammatical Evolution.- Grammar Based Feature Generation.- Application of Grammar Framework to Time-series Prediction.- Case Studies.- Conclusion.
First book presenting the framework for context-free grammar-based feature generation
Equips readers to predict time-series prediction using machine learning techniques
Includes case studies that illustrate the performance of different machine learning and model based approaches on financial, electrical and foreign exchange client trade volume time-series data
Includes supplementary material: sn.pub/extras
Date de parution : 03-2015
Ouvrage de 99 p.
15.5x23.5 cm
Disponible chez l'éditeur (délai d'approvisionnement : 15 jours).
Prix indicatif 52,74 €
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