Jyh-Horng Jeng

Pathways to Machine Learning and Soft Computing: 邁 向 機 器 學 習 與 軟 計 算 之 路 （ 國 際 英 文 版 ） Jyh-Horng Jeng

This book provides frequently studied and used machines together with soft computing methods such as evolutionary computation. The main topics of the machine learning cover Artificial Neural Networks (ANNs), Radial Basis Function Networks (RBFNs), Fuzzy Neural Networks (FNNs), Support Vector Machines (SVMs), and Wilcoxon Learning Machines (WLMs). The soft computing methods include Genetic Algorithm (GA) and Particle Swarm Optimization (PSO).

The contents are basics of machine learning, including construction of models and derivation of learning algorithms. This book also provides lots of examples, figures, illustrations, tables, exercises, and the solution menu. In addition, the simulated and validated codes written in R are also provided for the user to learn the programming procedure when written in different programming languages. The R codes work correctly on many simulated datasets. So, the readers can verify their own codes by comparison. Reading this book will become strong.

One most important feature of this book is that we provide step by step illustrations for every algorithm, which is referred to as pre-pseudo codes. The pre-pseudo codes arrange complicated algorithms in the forms of mathematical equations, which are ready for programming using any languages. It means that students and engineers can easily implement the algorithms from the pre-pseudo codes even they do not fully understand the underlying ideas. On the other hand, implementing the pre-pseudo codes will help them to understand the ideas.




本書將介紹常用的機器學習(machine learning)方法以åŠè»Ÿè¨ˆç®—(soft computing)如演化計算(evolutionary computation)等。主è¦çš„主題包括人工神經網路(Artificial Neural Network, ANN)ã€å¾‘å‘函數網路 (Radial Basis Function Network, RBFN)ã€æ¨¡ç³Šç¥žç¶“網路 (Fuzzy Neural Network, FNN)ã€æ”¯æ’å‘é‡æ©Ÿ (Support Vector Machine, SVM) ä»¥åŠ Wilcoxon 學習機 (Wilcoxon Learning Machine, WLM)等。軟計算方é¢çš„主題則包括基因演算法 (Genetic Algorithm, GA) 和粒å­ç¾¤èšæœ€ä½³åŒ– (Particle Swarm Optimization, PSO)。

本書的é‡é»žæ˜¯æ©Ÿå™¨å­¸ç¿’的基礎，包括模型的建立以åŠå­¸ç¿’演算法的的推導。åŒæ™‚也æ供許多的範例ã€åœ–示ã€è¡¨æ ¼ã€ç¿’題與解答。此外，é‡å°æ‰€æœ‰æ¼”算法，本書æ供使用 R 程å¼çš„實ç¾å’Œé©—證，這些 R 程å¼éƒ½ä½¿ç”¨æ¨¡æ“¬è³‡æ–™é©—è­‰æˆåŠŸï¼Œè®€è€…å¯ä»¥å¾ˆå®¹æ˜“使用其他的程å¼èªžè¨€ä¾†å¯¦ç¾ï¼Œä¸¦ä¸”å¯ä»¥è·Ÿæœ¬æ›¸æ‰€é™„帶的 R 程å¼ç¢¼äº¤å‰é©—證。讀完此書必然功力大增。

本書最é‡è¦çš„特色就是æ供所有演算法的 Pre-Pseudo Code，也就是說，使用類似程å¼èªžè¨€ Pseudo Code æ–¹å¼ï¼Œå°‡æ•¸å­¸å…¬å¼ä»¥æ­¥é©Ÿçš„æ–¹å¼è¡¨é”出來，éžå¸¸ç°¡æ˜“而且清楚，任何學生或工程師在還ä¸å®Œå…¨äº†è§£æ¼”算法的情形之下，就å¯ä»¥æ ¹æ“šæ‰€æ供的 Pre-Pseudo Code 使用å„種程å¼èªžè¨€ä¾†å¯¦ç¾ï¼›å¦ä¸€æ–¹é¢ï¼Œè®€è€…也å¯è—‰ç”±é€™æ¨£çš„實ç¾æ–¹å¼ä¾†ç†è§£æ¼”算法的推導。