Ulla B. Mogensen, Hemant Ishwaran, Thomas A. Gerds (2012). Evaluating Random Forests for Survival Analysis Using Prediction Error Curves. Journal of Statistical Software, 50(11), 1-23.
Abstract Prediction error curves are increasingly used to assess and compare predictions in survival analysis. This article surveys the R package pec which provides a set of functions for efficient computation of prediction error…
Added by Diego Marinho de Oliveira on April 10, 2015 at 12:21am — No Comments
From episode 10 of my Naked Analyst Channel on YouTube.
I think I do - and it is the ‘appification’ of analytics. What I mean by this is the reduction of a complex analytic activity such as market segmentation, down to a single button on your computer interface. Very much like the…Continue
In very simple words, the process of predicting the probability of an event using mathematical models is defined as predictive modelling. In different fields there has been a wide-spread application of predictive modelling. This is mainly for the purpose of decision making. Recently, the technological advancements have made it possible for predictive modelling to expands its reach within the healthcare sector.
Making right decisions at the right time is the success…Continue
Added by Ashish Soni on November 8, 2013 at 1:21am — No Comments
When was the last time your car made a funny noise or ran a little hotter than usual? Chances are, you quickly consulted a web browser for answers and found your way to a forum full of similar consumers and car enthusiasts, all eager to get answers to questions and argue over best solutions. A few pages through the conversation and you probably end up with a fairly educated guess as to whether a trip to a mechanic, or a car parts dealer, is in order.
Forums like the one mentioned are…Continue
Added by Radhika Subramanian on September 3, 2013 at 5:00am — No Comments
Data analysis echo system has grown all the way from SQL's to NoSQL and from Excel analysis to Visualization. Today, we are in scarceness of the resources to process ALL (You better understand what i mean by ALL) kind of data that is coming to enterprise. Data goes through profiling, formatting, munging or cleansing, pruning, transformation steps to analytics and predictive modeling. Interestingly, there is no one tool proved to be an effective solution to run…Continue
There is no question that the USA (in fact, most of the world) would be well-served with more quantitatively capable people to work in business and government. However, the current hysteria over the shortage of data scientists is overblown. To illustrate why, I am going to use an example from air travel.
On a recent trip from Santa Fe, NM to Phoenix, AZ, I tracked the various times:
Added by Neil Raden on June 27, 2012 at 10:00am — No Comments