spectrum
范围
The essece of machine learning:编程
Metaphor(比喻
): Credit approval
Applicant information:app
kind | info |
---|---|
age | 23 years |
gender | male |
annual salary | $30,000 |
years in residence | 1 year |
years in job | 1 year |
current debt | $15,000 |
... | ... |
可认为这是一个d-维向量
其元素依次是 salary, years in residence, years in job, current debt...
y在这里仅表示 extend credit (1) & not to extend credit (-1)
It is a function from domain X,
X is a set of all input x (the set of vectors of d-dimention), it's a d-dimention Euclidean space(欧氏空间
)
y : a binary co-demainendeavors
尽力
f is unknown, but g is known, and we credit it
the value of g is supposed to approximates f
为何须要hypothesis setdom
no downside for including a hypothesis set in the formalization, but there is an upsideide
no downside:函数
upside:idea
quadratic programming
二次编程???glorious
最好的,极好的pinpoint
精确查找spa
x1 salary, x2 years in residence, x3 years in job, x4 current debt ... xd ...
根据实际状况,分别给不一样的权重
视为credit scorethreshold
临界值3d
we start with random weights that will give a random linenotation
符号,记法
引入 x0 = 1 能够化简表达式code
经过这种方法,咱们尽量的使这些点被正确分类
只要是线性的,当迭代次数足够多后,总能所有分类正确component
premise
前提underlying process
基本过程
vending
贩卖
虽然没办法知道具体类别,可是能够作出分类
想这种样例少,为给出肯定函数的,实际上根据不一样规则是能够有不一样答案的