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BayesiaLabBayesiaLab User GuideMenusDataOpen Data SourceText FileStep 4 — Discretization and AggregationDiscretizationAutomatic DiscretizationDensity Approximation

Density Approximation

Context

Density Approximation is one of the Automatic Discretization algorithms for Continuous variables in Step 4 — Discretization and Aggregation of the Data Import Wizard.

Algorithm Details & Recommendations

The Density Approximation discretization detects changes in the sign of the derivative of the Probability Density Function (PDF) in order to identify local minima and maxima. Between each local minimum and maximum, the algorithm creates a threshold.

Density Approximation thresholds between local minima and maxima

The algorithm automatically detects the optimal number of bins, although you can specify the maximum number of bins. The minimum size permitted for bins is 1% of the data points.

Automatic DiscretizationEqual Distance