Ensemble Methods

Scorecards have long been used in business to provide easily understood measures of events and situations. A scorecard is literally a list of scores which can be summed to provide an overall rating. This rating is then used to inform a decision – whether to approve a loan or not…

Ensemble learning consists of creating multiple models and combining them to (hopefully) create a composite model that outperforms any individual component. This approach has been called by various commentators the most significant development in machine learning over the last decade. Building predictive models has traditionally involved the training of many…

  BigML offers a cloud based predictive analytics capability that is both refreshingly straightforward and extremely powerful. These two qualities are usually mutually exclusive, but by using decision trees and decision tree ensembles in conjunction with some very useful visualizations, the whole process of building and testing predictive models becomes…

Alpine Data Labs provides an enterprise solution to the problems of data access, model building, model deployment and model performance monitoring for predictive analytics applications. As data mining and machine learning technologies move out of the realm of esoterica, so organizations will need a full implementation and management environment. I spoke…

A list of random forest implementations, most of them open source / free. Apart from Salford Systems and Statistica most of the large commercial data mining packages have been slow to adopt, although SAS has recently introduced a random forest capability. Open Source / Free FastRandomForest for Weka Orange – part…