Machine learning for intelligent decision science
著者
書誌事項
Machine learning for intelligent decision science
（Algorithms for intelligent systems）
Springer, c2020
大学図書館所蔵 件 / 全5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
内容説明・目次
内容説明
The book discusses machine learning-based decision-making models, and presents intelligent, hybrid and adaptive methods and tools for solving complex learning and decision-making problems under conditions of uncertainty. Featuring contributions from data scientists, practitioners and educators, the book covers a range of topics relating to intelligent systems for decision science, and examines recent innovations, trends, and practical challenges in the field. The book is a valuable resource for academics, students, researchers and professionals wanting to gain insights into decision-making.
目次
Development of Different Machine Learning Ensemble Classifier for Gully Erosion Susceptibility in Gandheswari Watershed of West Bengal, India.- Classification of ECG Heartbeat using Deep Convolutional Neural Network.- Breast Cancer Identification and Diagnosis Techniques.- Energy Efficient Resource Allocation in Data Centers using a Hybrid Evolutionary Algorithm.- Root Cause Analysis using Ensemble Model for Intelligent Decision-Making.- Spider Monkey Optimization Algorithm in Data Science: A Quantifiable Objective Study.- Multi-Agent Based Systems In Machine Learning and Its Practical Case Studies.- Computer Vision and Machine Learning Approach for Malaria Diagnosis in Thin Blood Smears from Microscopic Blood Images.
「Nielsen BookData」 より