李宏毅Machine Learning学习笔记4 Classification: Probabilistic Generative Model

Classification 分类

分类要找一个function，输入就是对象 x ，输出是这个对象属于n个类别的哪一个。

• Credit Scoring
  
  • Input: income, savings, profession, age, past financial history ……
  • Output: accept or refuse
• Medical Diagnosis
  
  • Input: current symptoms, age, gender, past medical history ……
  • Output: which kind of diseases
• Handwritten character recognition
  
  • 8000多个汉字 8000多个class
• Face recognition
  
  • Input: image of a face, output: person

Example Application

神奇宝贝有很多的属性，比如电，火，水。要做的就是一个分类的问题：需要找到一个function，输入一只神奇宝贝，输出它是什么属性。

• HP: hit points, or health, defines how much damage a pokemon can withstand before fainting 35
• Attack: the base modifier for normal attacks (eg. Scratch,Punch) 55
• Defense: the base damage resistance against normal attacks 40
• SP Atk: special attack, the base modifier for special attacks (e.g. fire blast, bubble beam) 50
• SP Def: the base damage resistance against special attacks 50
• Speed: determines which pokemon attacks first each round 90

所以一只神奇宝贝可以用一个向量来表示，上述数字组成的向量。

How to do Classification

Classification as Regression