Machine learning : advances in research and applications
著者
書誌事項
Machine learning : advances in research and applications
(Computer science, technology and applications)
Nova Science Publishers, c2017
大学図書館所蔵 件 / 全2件
-
該当する所蔵館はありません
- すべての絞り込み条件を解除する
注記
Includes bibliographical references and index
内容説明・目次
内容説明
In chapter one, Lei Jia, PhD and Hua Gao, PhD analyze machine learning applications in small molecule and macromolecule drug discovery and development while comparing the similarities and differences between the two. They also examine their advantages and limitations with the intent to encourage further creative machine learning applications in drug discovery and development. During chapter two, Oscar Claveria, Enric Monte, and Salvador Torra present a study on the extrapolative performance of several machine learning models in a multiple-input multiple-output setting that permits cross-correlation between the inputs. Bojan Ploj, Germano Resconi, and Ali Yaghoubi parallel the solution of a system by logic gates and by a neural network, in which considerations are computed by the designated one step method during chapter three. In chapter four, Loris Nannia, Nicolo Zaffonatoa, Christian Salvatoreb, Isabella Castiglionib, and the Alzheimers Disease Neuroimaging Initiative propose a method that could aid in the early diagnosis of Alzheimers disease. Afterwards, F. Dornaika and I. Kamal Aldine present and experimentally assess two non-linear data self-representativeness coding schemes based on Hilbert space and column generation. Lastly, Christos Chrysoulas, Grigorios Kalliatakis, and Georgios Stamatiadis give an overview of Apache Hadoop, an open-source software framework used to distribute storage and process big data using the MapReduce programming model.
目次
- Preface
- Machine Learning in Drug Discovery & Development
- The Appraisal of Machine Learning Techniques for Tourism Demand Forecasting
- A One Step Method to Solving Brain Contradiction
- An Ensemble of Classifiers for the Early Diagnosis of Alzheimers Disease
- Instance Selection Using Non-linear Sparse Coding Schemes
- Hadoop & What It Is Good For
- Index.
「Nielsen BookData」 より