Class NoisyStats
java.lang.Object
dk.alexandra.fresco.stat.anonymisation.NoisyStats
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dk.alexandra.fresco.framework.builder.Computation<List<dk.alexandra.fresco.framework.DRes<dk.alexandra.fresco.lib.fixed.SFixed>>,dk.alexandra.fresco.framework.builder.numeric.ProtocolBuilderNumeric>
public class NoisyStats extends Object implements dk.alexandra.fresco.framework.builder.Computation<List<dk.alexandra.fresco.framework.DRes<dk.alexandra.fresco.lib.fixed.SFixed>>,dk.alexandra.fresco.framework.builder.numeric.ProtocolBuilderNumeric>
Compute differentially private estimates for the coefficients of a linear model fitted on a
dataset. The method is based on the paper Differentially
Private Simple Linear Regression by Alabi et. al.
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Constructor Summary
Constructors Constructor Description NoisyStats(List<dk.alexandra.fresco.framework.DRes<dk.alexandra.fresco.lib.fixed.SFixed>> x, List<dk.alexandra.fresco.framework.DRes<dk.alexandra.fresco.lib.fixed.SFixed>> y, double epsilon) -
Method Summary
Modifier and Type Method Description dk.alexandra.fresco.framework.DRes<List<dk.alexandra.fresco.framework.DRes<dk.alexandra.fresco.lib.fixed.SFixed>>>buildComputation(dk.alexandra.fresco.framework.builder.numeric.ProtocolBuilderNumeric root)
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Constructor Details
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Method Details
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buildComputation
public dk.alexandra.fresco.framework.DRes<List<dk.alexandra.fresco.framework.DRes<dk.alexandra.fresco.lib.fixed.SFixed>>> buildComputation(dk.alexandra.fresco.framework.builder.numeric.ProtocolBuilderNumeric root)- Specified by:
buildComputationin interfacedk.alexandra.fresco.framework.builder.Computation<List<dk.alexandra.fresco.framework.DRes<dk.alexandra.fresco.lib.fixed.SFixed>>,dk.alexandra.fresco.framework.builder.numeric.ProtocolBuilderNumeric>
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