## Ideology

Old day people study probability forcus on sample distribute. [fix parameters]
Bayes probability study forcus on parameters.[fix samples]

the new experiment result will refresh people cognition on old things.
It’s fit people cognition law on nation explor method.

## formula

First:

the probability event A, event B happen at the same time
, equals the probability A happen multiply with the probability
B happen when A happen.

So we have:

=>

=>

a new knowledge = a priori knowledge * a new factor affect knowledge / a new factor

We use sample experiment’s phenomenon verify rules.
Use adjust factor to adust parameters, make rules more accurate.

## Example

We need to check a rule:
watermelon sugar content > 10, good probability is 70%

1. prior condition is good watermelon probability is 20%
2. exp:bad watermelon has probability 25%, sugar content > 10
3. exp:good watermelon has probability 99%, sugar content > 10

so we have :

Now we found the threshold is not right, base on adjust factor, we change rule:
watermelon sugar content > 15, good probability is 70%

1. prior condition is good watermelon probability is 20%
2. exp:bad watermelon has probability 15%, sugar content > 15
3. exp:good watermelon has probability 90%, sugar content > 15

so we have :