November 2017
Intermediate to advanced
328 pages
6h 51m
Japanese
Content preview from 入門 PySpark ―PythonとJupyterで活用するSpark 2エコシステム
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88
5
章
MLlib
5.4.2
トレーニングおよびテストデータの切り出し
モデリングの段階に進む前に、トレーニングに使う分とテストに使う分にデータセットを分割してお
かなければなりません。ありがたいことに、RDDにはその処理を行ってくれる
.randomSplit(...)
という便利なメソッドがあります。このメソッドは比率のリストを引数に取り、それにしたがってデータ
セットをランダムに分割してくれます。
使い方は次のとおりです。
births_train, births_test = births_hashed.randomSplit([0.6, 0.4])
これだけです！ これ以上は何も必要ありません。
5.5
幼児の生存率の予測
いよいよ幼児の生存率の予測に進みましょう。このセクションでは、線形のクラシファイアーである
ロジスティック回帰と、非線形のクラシファイアーであるランダムフォレストという 2つのモデルを構築
します。前者の場合は使える特徴をすべて使いますが、後者については
ChiSqSelector(...)
メソッ
ドを利用し、上位の 4つの特徴だけを選択します。
5.5.1
MLlib
でのロジスティック回帰
ロジスティック回帰は、あらゆるクラシフィケーションのモデルを構築する上でベンチマークとなる
ものです。MLlib では確率的勾配降下法（Stochastic Gradient Descent = SGD）を使って推定された
ロジスティック回帰のモデルを提供していましたが、Spark ...
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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.
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.