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Predictive Analytics Toolbox

Among the years, hundreds of predictive techniques have been developed. They all have their advantages and drawbacks. There is no best choice that covers all data mining applications.Usually, the choice of the predictive algorithm depends on one (or...

Posted November 28, 2012    

Data Mining Book Review: Dance with Chance

If you ever worked on time series prediction (forecasting), you should read Dance with Chance. It is written by  a statistician, a psychologist and a decision scientist (Makriddakis, Hogarth and Gaba). As it is the case in The Numerati or Super...

Posted November 5, 2012    

Forecasting: Evaluation Criteria

To continue our series on forecasting, let’s discuss one of the varying factors: the evaluation criteria. In classification, the percentage of accuracy is often used. It is obvious and easy to interpret. In the case of regression (e.g. forecasting...

Posted October 16, 2012    

Swiss Association for Analytics

End of last year, I was invited to present at BaQMAR 2011. This exciting event was organized by a group of Belgium Analytics fans. Back in Switzerland, I felt the need for such an association. With the help of friends, experts in areas such as...

Posted October 1, 2012    

Forecasting: standard methods

To continue the first post of a series on forecasting, let’s discuss standard methods used for predicting time series. The two firsts methods can be used as benchmark for comparing with more advances models:Mean value: the mean of the time series...

Posted September 17, 2012    

Benefits of Using Data to Make Decisions: Guest Post by Erin Palmer

Today’s guest post is written by Erin Palmer from University Alliance. Thanks Erin for sharing your knowledge in the field of business intelligence and data mining.Benefits of Using Data to Make DecisionsIt has been said that what gets measured gets...

Posted June 11, 2012    

Outlier Detection in Two Review Articles (Part 1)

If you need to read two review articles about outlier detection, the first one is…Outlier Detection: A SurveyThe first one, Outlier Detection: A Survey, is written by Chandola, Banerjee and Kumar. They define outlier detection as the problem of...

Posted May 15, 2012    

Data Mining Interview: Meta Brown

Meta Brown, General Manager of Analytics at LinguaSys, has kindly accepted to answer a few questions for Data Mining Research. I would like to thank Meta for her time and her advices in Analytics.Data Mining Research: Who are you and what is your...

Posted April 30, 2012    

Data Mining Book Review: The Value of Business Analytics

Today’s book review is about The Value of Business Analytics – Identifying The Path to Profitability, from Evan Stubbs. I won’t keep any suspense: the book is excellent! It’s a must have for any person trying to apply analytics within a company...

Posted April 13, 2012    

Data Mining Book Review: Handbook of Statistical Analysis and Data Mining Applications

The book from Robert Nisbet, John Elder and Gary Miner is a fresh addition to any data miner library. First surprise: the book is in full colors with a lot of pictures which is a good point. With a focus on data mining applications, the book also...

Posted March 12, 2012    

Selling Data Mining to Management

Preparing data and building data mining models are two very well documented steps of analytics projects. However, whatever interesting your results are, they are useless if no action is taken. Thus, the step from analytics to action is a crucial one...

Posted February 19, 2012    

Data Mining Guest Post: Eric Greenwood

Today, Eric Greenwood, expert in data storage, is our guest blogger on Data Mining Research. Thanks for his post and feel free to comment about his input. Data Mining, Refining, and Storage As companies are able to more effectively store and...

Posted January 27, 2012