Week #13 – Data Product

A data product is a product or service whose value is derived from using algorithmic methods on data, and which in turn produces data to be used in the same product, or tangential data products.

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Week #12 – Dependent and Independent Variables

 

 

Statistical models normally specify how one set of variables, called dependent variables, functionally depend on another set of variables, called independent variables.

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Week #11 – Distance

Statistical distance is a measure calculated between two records that are typically part of a larger dataset, where rows are records and columns are variables.  To calculate...

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Week #10 – Decile Lift

In predictive modeling, the goal is to make predictions about outcomes on a case-by-case basis:  an insurance claim will be fraudulent or not, a tax return will be correct or in error, a subscriber...

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Week #9 – Decision Trees

In the machine learning community, a decision tree is a branching set of rules used to classify a record, or predict a continuous value for a record.  For example

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Week #8 – Feature Selection

In predictive modeling, feature selection, also called variable selection, is the process (usually automated) of sorting through variables to retain variables that are likely...

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Week #7 – Bagging

In predictive modeling, bagging is an ensemble method that uses bootstrap replicates of the original training data to fit predictive models.

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Week #6 – Boosting

In predictive modeling, boosting is an iterative ensemble method that starts out by applying a classification algorithm and generating classifications.

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Week #5 – Ensemble Methods

In predictive modeling, ensemble methods refer to the practice of taking multiple models and averaging their predictions.

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