Sunday, June 7, 2015

Quantifying the Efficacy of Machine Learning Algorithms

There are many articles and books and talks and so on all making claims about machine learning algorithms. Out of those, how many actually QUANTIFY THE EFFICACY OF THE ALGORITHM?.

Below are some references which will hopefully save people some leg work and help others quantify the performance of their algorithms.
  1. Articles
  2. Books
    1. Assessing and Improving Prediction and Classification by Timothy Masters
    2. Evaluating and Comparing the Performance of Machine Learning Algorithms by Melanie Mitchell
    3. Evaluating Learning Algorithms: A Classification Perspective by Japkowicz, Shah
      1. Amazon
        1. Customer Reviews
          1. Howard B. Bandy on July 7, 2014
            1. ... examples presented are all of stationary data ...
        2. Cambridge.Org
          1. Looking for an examination copy?
            1. If you are interested in the title for your course we can consider offering an examination copy. To register your interest please contact collegesales@cambridge.org providing details of the course you are teaching.
          2. Google
            1. Has table of contents and you can look at some randomly selected pages
            2. MohakShah.Com
              1. Email Address: eval@mohakshah.com
                1. For electronic editions, ...
                  1. Computing Resources
              2. Evaluation and Analysis of Supervised Learning Algorithms and Classifiers by Niklas Lavesson
                1. Machine Learning and Data Mining: 14 Evaluation and Credibility by Pier Luca Lanzi