September 2014
Intermediate to advanced
236 pages
4h 17m
Japanese
Content preview from Think Bayes ―プログラマのためのベイズ統計入門
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144
■
12
章
証拠
self.exam = exam
self.score = score
# start with the prior distribution
for p_correct, prob in exam.prior.Items():
self.Set(p_correct, prob)
# update based on an exam score
self.Update(score)
__
init
__
は、
Exam
オブジェクトとスケール化得点とを取る。事前確率分布のコピー
を作り、試験得点に基づいて、それ自身を更新する。
いつものように、
Suite
から
Update
を継承し、
Likelihood
を提供する。
def Likelihood(self, data, hypo):
p_correct = hypo
score = data
k = self.exam.Reverse(score)
n = self.exam.max_score
like = thinkbayes.EvalBinomialPmf(k, n, p_correct)
return like
hypo
は、
p_correct
の仮説値で、
data
はスケール化得点である。
物事を単純にしておくために、基本得点を正答数と解釈して、誤答のペナルティ（引
き算分）を無視する。この単純化によって、尤度は
n
個の問題で
k
個正答する確率を計
算する二項分布によって与えられる。
12.4
事後確率
図12-2は、試験得点に基づ ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.