August 2015
Intermediate to advanced
312 pages
7h 28m
Japanese
Content preview from 初めてのSpark
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227
11.4 データ型
おわかりの通り、このコードはどの言語でもよく似ています。このコードは、直接
RDD
を操作
しています。この場合は、文字列の
RDD
（オリジナルのテキスト）と
LabeledPoints
（ラベル付
きの特徴ベクトルのための
MLlib
のデータ型）が操作されている
RDD
です。
11.4
データ
MLlib
には、いくつかの固有のデータ型があります。それらは、
org.apache.spark.mllib
パッ
ケージ（
Java/Scala
）と、
pyspark.mllib
（
Python
）にあります。主な型を次に紹介します。
Vector
数学的なベクトルです。
MLlib
は、すべてのエントリを保存する密なベクトルと、
0
以外のエ
ントリだけを保存し、領域を節約する疎なベクトルを、共にサポートしています。このすぐ後
に、さまざまな型のベクトルについて議論します。ベクトルは、
mllib.linalg.Vectors
クラ
スを使って構築できます。
LabeledPoint
分類や回帰といった、教師あり学習アルゴリズムのためのラベル付きのデータ点です。特徴ベ
クトルとラベル（これは浮動小数点数です）を含みます。
mllib.regression
パッケージにあ
ります。
Rating
ユーザーによる製品の評価です。製品のレコメンデーション用に、
mllib.recommendation
パッ
ケージで使われています。
Model
各
Model
は、トレーニングアルゴリズムの結果であり、通常は
predict()
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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.