I received an email from software vendor Salford Systems the other day announcing new training classes for their data mining and predictive analytics product SPM, Salford Predictive Modeler. SPM 7 supports a number of the latest and most powerful statistical learning models developed by academics at Stanford and Cal, the two top-rated statistics departments – hence the name Salford. The "bible" that underpins much of this work, "The Elements of Statistical Learning," was co-authored by Stanford stats faculty Trevor Hastie, Robert Tibshirani and Jerome Friedman.

SPM is all about supervised learning, in which a number of inputs, predictors, independent variables or features are used to predict outputs, responses or dependent variables. The features and responses can be either qualitative, such as gender, or quantitative, like income. Problems for which the response is qualitative are known as classifications; where the output is quantitative they're called regressions. The models supported by SPM readily handle both.

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