April 2017
Intermediate to advanced
532 pages
12h 39m
English
book
Machine Learning with Spark - Second Edition
by Rajdeep Dua, Brian O'Neill, Stephen Boesch, Manpreet Singh Ghotra, Nick Pentreath
Content preview from Machine Learning with Spark - Second Edition
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WSSSE and iterations
In this section, we evaluate the effect or iterations on WSSSE for bisecting the K-means algorithm.
The source code is:
object BisectingKMeansMetrics { case class RatingX(userId: Int, movieId: Int, rating: Float, timestamp: Long) val DATA_PATH= "../../../data/ml-100k" val PATH_MOVIES = DATA_PATH + "/u.item" val dataSetUsers = null def main(args: Array[String]): Unit = { val spConfig = ( new SparkConf).setMaster("local[1]").setAppName("SparkApp"). set("spark.driver.allowMultipleContexts", "true") val spark = SparkSession .builder() .appName("Spark SQL Example") .config(spConfig) .getOrCreate() val datasetUsers = spark.read.format("libsvm").load( "./data/movie_lens_libsvm/movie_lens_users_libsvm/part-Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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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.