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You're reading from  Clojure for Data Science

Product typeBook
Published inSep 2015
Reading LevelIntermediate
Publisher
ISBN-139781784397180
Edition1st Edition
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Author (1)
Henry Garner
Henry Garner
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Henry Garner

Henry Garner is a graduate from the University of Oxford and an experienced developer, CTO, and coach. He started his technical career at Britain's largest telecoms provider, BT, working with a traditional data warehouse infrastructure. As a part of a small team for 3 years, he built sophisticated data models to derive insight from raw data and use web applications to present the results. These applications were used internally by senior executives and operatives to track both business and systems performance. He then went on to co-found Likely, a social media analytics start-up. As the CTO, he set the technical direction, leading to the introduction of an event-based append-only data pipeline modeled after the Lambda architecture. He adopted Clojure in 2011 and led a hybrid team of programmers and data scientists, building content recommendation engines based on collaborative filtering and clustering techniques. He developed a syllabus and copresented a series of evening classes from Likely's offices for professional developers who wanted to learn Clojure. Henry now works with growing businesses, consulting in both a development and technical leadership capacity. He presents regularly at seminars and Clojure meetups in and around London.
Read more about Henry Garner

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The normal equation


Now that we've covered the basics of matrix and vector manipulation we're in a position to study the normal equation. This is an equation that uses matrix algebra to calculate the coefficients of our OLS linear regression model:

We read "to find β, multiply the inverse of X transpose X, by X transpose y" where X is the matrix of independent variables (including the intercept term) for our sample and y is a vector containing the dependent variables for our sample. The result β contains the calculated coefficients. This normal equation is relatively easy to derive from the equation of multiple regression, applying the rules of matrix multiplication, but the mathematics is beyond the scope of this book.

We can implement the normal equation with Incanter using only the functions we have just encountered:

(defn normal-equation [x y]
  (let [xtx  (i/mmult (i/trans x) x)
        xtxi (i/solve xtx)
        xty  (i/mmult (i/trans x) y)]
    (i/mmult xtxi xty)))

This normal equation...

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Clojure for Data Science
Published in: Sep 2015Publisher: ISBN-13: 9781784397180

Author (1)

author image
Henry Garner

Henry Garner is a graduate from the University of Oxford and an experienced developer, CTO, and coach. He started his technical career at Britain's largest telecoms provider, BT, working with a traditional data warehouse infrastructure. As a part of a small team for 3 years, he built sophisticated data models to derive insight from raw data and use web applications to present the results. These applications were used internally by senior executives and operatives to track both business and systems performance. He then went on to co-found Likely, a social media analytics start-up. As the CTO, he set the technical direction, leading to the introduction of an event-based append-only data pipeline modeled after the Lambda architecture. He adopted Clojure in 2011 and led a hybrid team of programmers and data scientists, building content recommendation engines based on collaborative filtering and clustering techniques. He developed a syllabus and copresented a series of evening classes from Likely's offices for professional developers who wanted to learn Clojure. Henry now works with growing businesses, consulting in both a development and technical leadership capacity. He presents regularly at seminars and Clojure meetups in and around London.
Read more about Henry Garner