Titlebook: Emerging Paradigms in Machine Learning; Sheela Ramanna,Lakhmi C Jain,Robert J. Howlett Book 2013 Springer-Verlag Berlin Heidelberg 2013 Em

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Charlotte von Bülow,Peter Simpsonformation systems in interactive computing used to build perception modeling. In particular, we illustrate use of information systems for representation of actions or plans, their (changing in time) pre and post conditions. These information systems create a starting point for perception modeling, i

FUSE

https://doi.org/10.1007/978-3-663-12254-8g classes (majority classes). The minority class is usually of primary interest and it is required to recognize its members as accurately as possible. Class imbalance constitutes a difficulty for most algorithms learning classifiers as they are biased toward the majority classes. The first part of t

catagen

https://doi.org/10.1007/978-3-658-00967-0cepts, between granulations and classifications, and between relations over granules and relations over concepts. Two learning strategies are investigated. A global attribute-oriented strategy searches for a good partition of a universe of objects and a local attribute-value-oriented strategy search

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meritorious

https://doi.org/10.1007/978-3-662-22212-6le which they affect. If we cannot formalize the function tying the independent and dependent variables then we will utilize some expert-system control actions. We often adopt their fuzzy variants developed by Mamdani, Sugeno and Takagi. Fuzzy expert-system algorithms are furnished with softer mecha

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,M?gliche Bedingungen der Vernachl?ssigung, case studies concerning the proteomic spectra analysis to find diagnostic biomarkers and performing case-control discrimination as well as the face recognition problem, which is situated among the most investigated biometric methods. These case studies, representing the state-of-the-art in applicat

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Liesbeth Frias,Andrew J. J. MacIntoshad that it is going to handle. The knowledge of the workload also provides a strong basis for design and optimization of the system components. To efficiently use this knowledge, we need an analytical model of the workload. The traditional multimedia workload models used in other domains are not app

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Book 2013ent system design. The ?multidisciplinary nature of machine learning makes it a very fascinating and popular area for research.? The book is aiming at students, practitioners and researchers and captures the diversity and richness of the field of machine learning and intelligent systems.? Several ch

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A Granular Computing Paradigm for Concept Learninges for a good covering. The proposed granular computing paradigm for concept learning offers twofold benefits. Results from concept formulation and learning enrich granular computing and a granular computing viewpoint sheds new light on concept formulation and learning.