Machine Learning Paradigms

Applications of Learning and Analytics in Intelligent Systems

AvGeorge A. Tsihrintzis,Maria Virvou

Häftad, Engelska, 2020

Del 1 i serien Learning and Analytics in Intelligent Systems

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Beskrivning

This book is the inaugural volume in the new Springer series on Learning and Analytics in Intelligent Systems. accordingly, the new series encourages an integrated approach to themes and topics in these disciplines, which will result in significant cross-fertilization, research advances and new knowledge creation.

Produktinformation

Utgivningsdatum:2020-08-14
Mått:155 x 235 x 31 mm
Vikt:850 g
Format:Häftad
Språk:Engelska
Serie:Learning and Analytics in Intelligent Systems
Antal sidor:548
Förlag:Springer Nature Switzerland AG
ISBN:9783030156305

Utforska kategorier

Systemvetenskap och AI inom Data och IT

Innehållsförteckning

Chapter 1: Machine Learning Paradigms: Applications of Learning and Analytics in Intelligent Systems.- Chapter 2: A Comparison of Machine Learning Techniques to Predict the Risk of Heart Failure.- Chapter 3: Differential gene Expression Analysis of RNA-seq Data Using Machine Learning for Cancer Research.- Chapter 4: Machine Learning Approaches for Pap-Smear Diagnosis: An Overview.- Chapter 5: Multi-Kernel Analysis Paradigm Implementing the Learning from Loads Approach for Smart Power Systems.- Chapter 6: Conceptualizing and Measuring Energy Security: Geopolitical Dimensions, Data Availability, Quantitative and Qualitative Methods.- Chapter 7: Automated Stock Price Motion Prediction Using Technical Analysis Datasets and Machine Learning.- Chapter 8: Airport Data Analysis Using Common Statistical Methods and Knowledge-Based Techniques.- Chapter 9: A Taxonomy and Review of the Network Data Envelopment Analysis Literature.- Chapter 10: Applying Advanced Data Analytics and Machine Learning to Enhance the Safety Control of Dams.- Chapter 11: Analytics and Evolving Landscape of Machine Learning for Emergency Response.- Chapter 12: Social Media Analytics, Types and Methodology.- Chapter 13: Machine Learning Methods for Opinion Mining in Text: The Past and the Future.- Chapter 14: Ship Detection Using Machine Learning and Optical Imagery in the Maritime Environment.- Chapter 15: Video Analytics for Visual Surveillance and Applications: An Overview and Survey.- Chapter 16: Machine Learning in Alternate Testing of Integrated Circuits