PRML 读书笔记-Chapter1

reinforcement learning

Finding suitable actions to take in a given situation in order to maximize a reward.

A general feature of reinforcement learning is the trade-off between exploration,in which the system tries out new kinds of actions to see how effective they are,and exploitation, in which the system makes use of actions that are known to yield a high reward.

Too strong a focus on either exploration or exploitation will yield poor results.

linear models

Functions,such as the polynomial,which are linear in the unknown parameters have important properties and are called linear model.

for instance:

y(x,W) = w0 + w1*x + w2*x2 + w3*x3 + … + wm*xm

Error function

The values of the coefficients will be determined by fitting the polynomial to the training data.This can be done by minimization an error function the measures the misfit between the function y(x,W),for any given value of W, and the training set data points.

##Root - Mean -Square##

RMS,defined by