Machine Learning: Advances in Research and Applications

Roger Inge (Editor)
Jan Leif (Editor)

Series: Computer Science, Technology and Applications
BISAC: COM037000




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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, Nicolò Zaffonatoa, Christian Salvatoreb, Isabella Castiglionib, and the Alzheimer’s Disease Neuroimaging Initiative propose a method that could aid in the early diagnosis of Alzheimer’s 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. (Imprint: Nova)


Chapter 1. Machine Learning in Drug Discovery and Development (pp. 1-58)
Lei Jia and Hua Gao

Chapter 2. The Appraisal of Machine Learning Techniques for Tourism Demand Forecasting (pp. 59-90)
Oscar Claveria, Enric Monte and Salvador Torra

Chapter 3. A One Step Method to Solving Brain Contradiction (pp. 91-144)
Bojan Ploj, Germano Resconi and Ali Yaghoubi

Chapter 4. An Ensemble of Classifiers for the Early Diagnosis of Alzheimer’s Disease (pp. 145-160)
Loris Nanni, Nicolò Zaffonato, Christian Salvatore, Isabella Castiglioni and the Alzheimer's Disease Neuroimaging Initiative

Chapter 5. Instance Selection Using Non-linear Sparse Coding Schemes (pp. 161-176)
F. Dornaika and I. Kamal Aldine

Chapter 6. Hadoop and What It Is Good For (pp. 177-194)
Christos Chrysoulas, Grigorios Kalliatakis and Georgios Stamatiadis

Index (pp. 195)

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