November 2018
Intermediate to advanced
272 pages
6h 51m
Japanese
book
エレガントなSciPy ―Pythonによる科学技術計算
by Juan Nunez-Iglesias, Stéfan van der Walt, Harriet Dashnow, 山崎 邦子, 山崎 康宏
Content preview from エレガントなSciPy ―Pythonによる科学技術計算
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135
5.6 情報理論の概要
しいでしょうけど）、代わりに以下の年表を使います。
WeatherSpark
（
http://bit.ly/2sXj4D9
）
から見積もったものです。
月
P
（雨）
P
（晴）
1 0.25 0.75
2 0.27 0.73
3 0.24 0.76
4 0.18 0.82
5 0.14 0.86
6 0.11 0.89
7 0.07 0.93
8 0.08 0.92
9 0.10 0.90
10 0.15 0.85
11 0.18 0.82
12 0.23 0.77
したがって、
month
が与えられたときの
rain
の条件付きエントロピーは、以下のようになりま
す。
H(R|M)
= −
1
12
0.25 log
2
(0.25)+0.75 log
2
(0.75) −
1
12
0.27 log
2
(0.27)+0.73 log
2
(0.73)
−
...
−
1
12
0.23 log
2
(0.23)+0.77 log
2
(0.77)
≒
0.626ビット
したがって、月の情報を用いると信号の無作為性は減りますが、たいして減りません。
また、
rain
が与えられた場合の
month
の条件付きエントロピーも計算できます。これは、雨が
降ったとわかっていれば、月を特定するのにどれだけの情報が必要かを計るものです。直観的に
は、何の前知識もなく臨むよりはマシだということはわかります。なぜなら、冬季の方が降雨確率
が高いからです。
5.6.1
演習：条件付きエントロピーの計算
降雨情報が与えられた場合の月の条件付きエントロピーを計算してみましょう。月変数のエント ...
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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.
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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.