Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Survey: Machine Learning Projects Still Routinely Fail to Deploy
 Originally published in KDnuggets. Eric Siegel highlights the chronic...
Three Best Practices for Unilever’s Global Analytics Initiatives
    This article from Morgan Vawter, Global Vice...
Getting Machine Learning Projects from Idea to Execution
 Originally published in Harvard Business Review Machine learning might...
Eric Siegel on Bloomberg Businessweek
  Listen to Eric Siegel, former Columbia University Professor,...

fraud prediction

Predicting Fraud: Another Not So Easy Task

 As I have stated in previous articles, the most difficult challenge in building predictive models is the creation of the analytical file. Typically, this comprises between 80%-90% of the data scientist’s time with 10%-20%  comprising the actual run or runs of the different mathematical/statistical algorithms. In the creation of the analytical file, the two elements