Data-Driven Computational Neuroscience:Machine Learning and Statistical Models

数据驱动的计算神经科学:机器学习和统计模型

计算机科学技术基础学科

原   价:
920
售   价:
736.00
优惠
平台大促 低至8折优惠
发货周期:预计5-7周发货
作      者
出  版 社
出版时间
2020年08月31日
装      帧
精装
ISBN
9781108493703
复制
页      码
700
语      种
英文
综合评分
暂无评分
我 要 买
- +
库存 50 本
  • 图书详情
  • 目次
  • 买家须知
  • 书评(0)
  • 权威书评(0)
图书简介
Data-driven computational neuroscience facilitates the transformation of data into insights into the structure and functions of the brain. This introduction for researchers and graduate students is the first in-depth, comprehensive treatment of statistical and machine learning methods for neuroscience. The methods are demonstrated through case studies of real problems to empower readers to build their own solutions. The book covers a wide variety of methods, including supervised classification with non-probabilistic models (nearest-neighbors, classification trees, rule induction, artificial neural networks and support vector machines) and probabilistic models (discriminant analysis, logistic regression and Bayesian network classifiers), meta-classifiers, multi-dimensional classifiers and feature subset selection methods. Other parts of the book are devoted to association discovery with probabilistic graphical models (Bayesian networks and Markov networks) and spatial statistics with point processes (complete spatial randomness and cluster, regular and Gibbs processes). Cellular, structural, functional, medical and behavioral neuroscience levels are considered.
本书暂无推荐
本书暂无推荐
看了又看
  • 上一个
  • 下一个