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Clojure for Data Science

You're reading from   Clojure for Data Science Statistics, big data, and machine learning for Clojure programmers

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Product type Paperback
Published in Sep 2015
Publisher
ISBN-13 9781784397180
Length 608 pages
Edition 1st Edition
Languages
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Author (1):
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Henry Garner Henry Garner
Author Profile Icon Henry Garner
Henry Garner
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Toc

Table of Contents (12) Chapters Close

Preface 1. Statistics FREE CHAPTER 2. Inference 3. Correlation 4. Classification 5. Big Data 6. Clustering 7. Recommender Systems 8. Network Analysis 9. Time Series 10. Visualization Index

Parse the data

Since the data will all fit in the main memory for convenience, we'll define several functions that will load the ratings into Clojure data structures. The line->rating function takes a line, splits it into fields where a tab character is found, converts each field to a long datatype, then uses zipmap to convert the sequence into a map with the supplied keys:

(defn to-long [s]
  (Long/parseLong s))

(defn line->rating [line]
  (->> (s/split line #"\t")
       (map to-long)
       (zipmap [:user :item :rating])))

(defn load-ratings [file]
  (with-open [rdr (io/reader (io/resource file))]
    (->> (line-seq rdr)
         (map line->rating)
         (into []))))

(defn ex-7-3 []
  (->> (load-ratings "ua.base")
       (first)))

;; {:rating 5, :item 1, :user 1}

Let's write a function to parse the u.items file as well, so that we know what the movie names are:

(defn line->item-tuple [line]
  (let [[id name] (s/split line...
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