Machine Learning Research Progress de Hannah Peters

Machine Learning Research Progress

Hannah Peters

Mia Vogel

As a broad subfield of artificial intelligence, machine learning is concerned with the design and development of algorithms and techniques that allow computers to "learn". At a general level, there are two types of learning: inductive, and deductive. Inductive machine learning methods extract rules and patterns out of massive data sets. The major focus of machine learning research is to extract information from data automatically, by computational and statistical methods. Hence, machine learning is closely related not only to data mining and statistics, but also theoretical computer science. This book presents new and important research in this field.

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Cuprins

Preface; Machine Learning Approaches in Promoter Sequence Analysis; Recent Advances in Machine Learning for Financial Markets; A Review of Bankruptcy Prediction Models: The Machine Learning Perspective; Application of Learning Machines and Combinatorial Algorithms in Water Resources Management and Hydrologic Sciences; Machine Learning Techniques to Identify Marker Genes for Diagnostic Classification of Microarrays; Using Ensemble of Classifiers in Bioinformatics; Evolving Rules From Neural Networks Trained on Binary and Continuous Data; Machine Learning in Automatic Speech Recognition: Boosting and Discriminative Training of the Acoustic Model; Machine Learning for Knowledge Derived from the Paucity of Data; Evaluating the Computational Requirements of Using SVM Software to Train Data-Intensive Problems; Reservoir Computing for Sensory Prediction and Classification in Adaptive Agents; Boosting Linear Graph Embedding for Dimensionality Reduction; Expert Networks with Mixed Continuous and Categorical Feature Variables: A Location Modeling Approach; Applicability of Statistical Learning Algorithms for Predicting Skin Friction Capacity of Driven Piles in Clay; Learning Methods for Spam Filtering; Learning Support Vector Regression Models for Fast Radiation Dose Rate Calculations; Is the Parts-Based Concept of NMF Relevant for Object Recognition Tasks?; Index.