- 电子工业出版社
- 9787121500190
- 1-1
- 560130
- 平塑
- 16开
- 2025-04
- 326
- 204
- 计算机科学与技术
- 本科 研究生及以上
内容简介
本书是机器学习的入门书，深入浅出地讲解机器学习的基础理论与应用，不仅注重给理论添加浅显易懂的解释和详述，而且探讨何种创新思维或科学思维可以产生或引导出某个理论，让学习者在学习理论过程中自然地培养创新思维与科学思维。本书知识点包括回归分析、k-近邻算法、决策树、贝叶斯分类器、支持向量机、模型性能评估、集成学习、降维方法、聚类、EM 算法与高斯混合模型、神经网络与深度学习等。本书每章都设计手工计算的应用例题，以演示理论解题和计算过程，帮助学习者理解和掌握理论。每章配有编程实践的实例，不仅示范解题的Python 代码，还示范解题思路、步骤和结果分析，培养学习者解决实际问题的能力。每章自然地融入科技强国、弘扬中华智慧与文化等内容。此外，每章的习题可巩固知识，对应的在线课程（中国大学MOOC，课程名：机器学习）可引领学习。 本书的配套教学资源有教学大纲、教学课件、源代码和案例素材等，读者可登录华信教育资源网免费下载；编程实例所用数据集在书中标注了下载途径。 本书可作为人工智能、计算机相关专业的教材，或供机器学习理论与应用的学习者使用参考。
目录
第1章 绪论···································································································1__eol__1.1 机器学习简介·······················································································2__eol__1.2 机器学习方法的分类··············································································5__eol__1.3 机器学习框架·······················································································7__eol__1.4 Python 的机器学习开发环境····································································9__eol__1.5 习题································································································· 10__eol__第2章 回归分析··························································································· 11__eol__2.1 一元线性回归····················································································· 11__eol__2.2 多元线性回归····················································································· 14__eol__2.3 多项式回归························································································ 16__eol__2.4 回归分析的效果评价············································································ 17__eol__2.5 逻辑回归··························································································· 19__eol__2.6 实例与编程求解·················································································· 22__eol__2.7 习题································································································· 26__eol__第3章 k-近邻算法························································································· 28__eol__3.1 k-近邻分类算法·················································································· 28__eol__3.2 k 值的选取························································································· 30__eol__3.3 距离度量··························································································· 31__eol__3.4 k-近邻回归算法·················································································· 31__eol__3.5 k-近邻算法的性能和特点······································································ 33__eol__3.6 实例与编程求解·················································································· 34__eol__3.7 习题································································································· 36__eol__第4章 决策树······························································································ 38__eol__4.1 决策树的原理····················································································· 38__eol__4.2 决策树的构造算法··············································································· 39__eol__4.3 信息熵······························································································ 43__eol__4.4 ID3 算法··························································································· 43__eol__4.5 C4.5 算法·························································································· 44__eol__4.6 CART 算法························································································ 45__eol__4.7 决策树的剪枝····················································································· 47__eol__4.8 决策树的特点····················································································· 48__eol__4.9 实例与编程求解·················································································· 48__eol__4.10 习题······························································································· 52__eol__第5章 贝叶斯分类器····················································································· 54__eol__5.1 概率相关知识····················································································· 54__eol__5.2 贝叶斯分类原理·················································································· 55__eol__5.3 朴素贝叶斯分类器··············································································· 56__eol__5.4 实例与编程求解······························································
