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Computational Methods of Feature Selection

issues, Computational Methods of Feature Selection introduces the basic concepts and principles, state-of-the-art algorithms, and novel;

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Hybrid Methods in Feature Selection

face the problem of intractable computational time. Since no single feature selection method could handle all requirements of feature selection;

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Computational Intelligence And Feature Selection

theories Computational Intelligence and Feature Selection is an ideal resource for advanced undergraduates, postgraduates, researchers, and;

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Biosignal Processing and Classification Using Computational Learning and Intelligence

selection/dimensionality reduction. Part Three presents the fundamentals of computational learning (machine learning). Then, the main techniques;

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Handbook of Bayesian Variable Selection

The Handbook of Bayesian Variable Selection provides a comprehensive review of theoretical, methodological and computational aspects;

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Data Analytics in Bioinformatics

Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine;

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Statistical Computing with R

Computational statistics and statistical computing are two areas that employ computational, graphical, and numerical approaches to solve;

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Data-Driven Computational Neuroscience

Data-driven computational neuroscience facilitates the transformation of data into insights into the structure and functions of the brain;

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Machine Learning in Bioinformatics

increasingly being used to address problems in computational biology and bioinformatics. Novel computational techniques to analyze high throughput data;

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Computational Methods in Synthetic Biology

This second edition book provides complete coverage of the computational approaches currently used in Synthetic Biology. New chapters;

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Computational Intelligence in Multi Feature Visual Pattern Recognition

This book presents a collection of computational intelligence algorithms that addresses issues in visual pattern recognition such as high;

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Feature Selection in Data Mining - Approaches Based on Information Theory

set of features will almost certainly overfit on future data sets. The book presents streamwise feature selection which interleaves the;

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Advances in Computational Techniques for Biomedical Image Analysis

Advances in Computational Techniques for Biomedical Image Analysis: Methods and Applications focuses on post-acquisition challenges;

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Feature Engineering and Computational Intelligence in ECG Monitoring

This book discusses feature engineering and computational intelligence solutions for ECG monitoring, with a particular focus on how these;

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Artificial Life and Computational Intelligence

This book constitutes the proceedings of the Second Australasian Conference on Artificial Life and Computational Intelligence, ACALCI;

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Natural Selection

This book summarizes the knowledge in the field of methods to identify signatures of natural selection. A number of mathematical models and;

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Natural Selection

This book summarizes the knowledge in the field of methods to identify signatures of natural selection. A number of mathematical models and;

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Optimization Approaches for Solving String Selection Problems

of optimization methods for string selection problems for young scientists and a detailed description of the mathematical and computational methods;

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Computational Medicinal Chemistry for Drug Discovery

Observing computational chemistry's proven value to the introduction of new medicines, this reference offers the techniques most frequently;

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Data Analytics for Protein Crystallization

categorization of crystallization image trials; introduces a selection of computational methods for protein crystallization screening, and the hardware;

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Applications in Statistical Computing

This volume presents a selection of research papers on various topics at the interface of statistics and computer science. Emphasis is put;

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Spectral Feature Selection for Data Mining

Spectral Feature Selection for Data Mining introduces a novel feature selection technique that establishes a general platform for studying;

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Spectral Feature Selection for Data Mining

Spectral Feature Selection for Data Mining introduces a novel feature selection technique that establishes a general platform for studying;

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Foundations of Computational Intelligence Volume 5

Foundations of Computational Intelligence Volume 5: Function Approximation and Classification Approximation theory is that area of analysis;

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Brain Seizure Detection and Classification Using EEG Signals

performance feature extraction. The book covers the feature selection method based on One-way ANOVA, along with high performance machine learning;

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Combining Pattern Classifiers

selection, now in its second edition The art and science of combining pattern classifiers has flourished into a prolific discipline since the first;

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Advances in Discretization Methods

intended to achieve higher computational efficiency and to account for special features of the solution directly in the approximation space and/or;

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