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Chapter and Conference Paper
A Comparison of Feature Selection Methods to Optimize Predictive Models Based on Decision Forest Algorithms for Academic Data Analysis
Nowadays, Feature Selection (FS) methods are essential (1) to create easy-to-explain predictive models in shorter periods of time, (2) to reduce overfitting and (3) avoid sparsity of data. The suitability of u...
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Chapter and Conference Paper
Evolving Mashup Interfaces Using a Distributed Machine Learning and Model Transformation Methodology
Nowadays users access information services at any time and in any place. Providing an intelligent user interface which adapts dynamically to the users’ requirements is essential in information systems. Convent...
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Chapter and Conference Paper
An Implementation of a Trading Service for Building Open and Interoperable DT Component Applications
Integration and interoperability of software components and information systems is extremely important nowadays to manage data and to integrate applications and information, and to improve business processes i...