| 书目名称 | Reverse Hypothesis Machine Learning |
| 副标题 | A Practitioner‘s Per |
| 编辑 | Parag Kulkarni |
| 视频video | |
| 概述 | Presents a practitioner’s perspective on knowledge innovation and machine learning.Discusses different aspects of knowledge innovation applied to systemic machine learning paradigms.Includes case stud |
| 丛书名称 | Intelligent Systems Reference Library |
| 图书封面 |  |
| 描述 | .This book introduces a paradigm of reverse hypothesis machines (RHM), focusing on knowledge innovation and machine learning. Knowledge- acquisition -based learning is constrained by large volumes of data and is time consuming. Hence Knowledge innovation based learning is the need of time. Since under-learning results in cognitive inabilities and over-learning compromises freedom, there is need for optimal machine learning. All existing learning techniques rely on mapping input and output and establishing mathematical relationships between them. Though methods change the paradigm remains the same—the forward hypothesis machine paradigm, which tries to minimize uncertainty. The RHM, on the other hand, makes use of uncertainty for creative learning. The approach uses limited data to help identify new and surprising solutions. It focuses on improving learnability, unlike traditional approaches, which focus on accuracy. The book is useful as a reference book for machine learning researchers and professionals as well as machine intelligence enthusiasts. It can also used by practitioners to develop new machine learning applications to solve problems that require creativity.. |
| 出版日期 | Book 2017 |
| 关键词 | Intelligent Systems; Knowledge Information; Systems Machine Learning; Creative Machines; Creative Machin |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-55312-2 |
| isbn_softcover | 978-3-319-85626-1 |
| isbn_ebook | 978-3-319-55312-2Series ISSN 1868-4394 Series E-ISSN 1868-4408 |
| issn_series | 1868-4394 |
| copyright | Springer International Publishing AG 2017 |
发表于 2025-3-21 19:25:57
