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
Talent Analytics uses data gathered from our own proprietary talent assessments as an input variable to predict hiring success – pre-hire. We treat this dataset just like any other dataset in our predictive work. We are careful...
In anticipation of her upcoming conference presentation, Crowd-Sourcing and Quality: How To Get The Best Out of Hand-Tagged Training Data for Machine Learning Models at Predictive Analytics World for Business New York, Oct 29-Nov 2, 2017, we...
From the perspective of data science, a Muslim ban would weaken security, not strengthen it (click for additional articles by Eric Siegel on analytics and social justice). Originally published by Scientific American June 14, 2017 Let’s not...
In anticipation of his upcoming conference presentation, Regulating Opacity: Solving for the Conflict Between Laws and Analytics at Predictive Analytics World for Business New York, Oct 29-Nov 2, 2017, we asked Andrew Burt, Chief Privacy Officer &...
In anticipation of his upcoming conference presentation, Acquisition Funnel for Higher Education at Predictive Analytics World for Business New York, Oct 29-Nov 2, 2017, we asked Feyzi Bagirov, Data Science Advisor at Metadata.io and Analytics Instructor, Harrisburg...
In anticipation of his upcoming keynote conference presentation, UPS’ Road to Optimization, at Predictive Analytics World for Business New York, Oct 29-Nov 2, 2017, we asked Jack Levis, Senior Director, Process Management at UPS, a few questions...
Employee Tenure in a “Survival Analytics” Framework With a cumulative cost curve in hand, we now turn to evaluate attrition. We hope to illustrate a far more intuitive and useful visualization than the popular business metric, annual...
In anticipation of his upcoming Predictive Analytics World Manufacturing Chicago, June 19-22, 2017 conference presentation, Closing the Loop with Predictive Product Performance, we interviewed Richard Semmes, Senior Director, R&D at Siemens PLM. View the Q-and-A below for a glimpse of what’s...
In anticipation of his upcoming conference presentation, How to Revolutionize Your Model Optimization, at Predictive Analytics World for Business Chicago, June 19-22, 2017, we asked Edward Shihadeh, Chief Data Officer at Auspice Analytics, LLC, a few questions...
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