[ML] First pass implementation of support functionality for change detection and modelling (#9)

This implements 1) a naive Bayes classifier, using our distribution models, which will be used 
for modelling the probability of a change, and 2) a change detector framework, currently 
supporting detecting level shifts and time shifts, which works by comparing BIC of the various 
possible hypotheses against one another and a null hypothesis that there is no change.

Author: tveasey

include/maths/CNaiveBayes.h

@@ -0,0 +1,228 @@
+/*
+ * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
+ * or more contributor license agreements. Licensed under the Elastic License;
+ * you may not use this file except in compliance with the Elastic License.
+ */
+
+#ifndef INCLUDED_ml_maths_CNaiveBayes_h
+#define INCLUDED_ml_maths_CNaiveBayes_h
+
+#include <maths/ImportExport.h>
+
+#include <maths/CPrior.h>
+
+#include <boost/unordered_map.hpp>
+
+#include <cstddef>
+#include <vector>
+
+namespace ml
+{
+namespace core
+{
+class CStatePersistInserter;
+class CStateRestoreTraverser;
+}
+namespace maths
+{
+struct SDistributionRestoreParams;
+
+//! \brief The interface expected by CNaiveBayes for implementations
+//! of the class conditional density functions.
+class MATHS_EXPORT CNaiveBayesFeatureDensity
+{
+    public:
+        using TDouble1Vec = core::CSmallVector<double, 1>;
+
+    public:
+        virtual ~CNaiveBayesFeatureDensity() = default;
+
+        //! Create and return a clone.
+        //!
+        //! \note The caller owns this.
+        virtual CNaiveBayesFeatureDensity *clone() const = 0;
+
+        //! Initialize by reading state from \p traverser.
+        virtual bool acceptRestoreTraverser(const SDistributionRestoreParams &params,
+                                            core::CStateRestoreTraverser &traverser) = 0;
+
+        //! Persist state by passing information to \p inserter.
+        virtual void acceptPersistInserter(core::CStatePersistInserter &inserter) const = 0;
+
+        //! Add the value \p x.
+        virtual void add(const TDouble1Vec &x) = 0;
+
+        //! Compute the log value of the density function at \p x.
+        virtual double logValue(const TDouble1Vec &x) const = 0;
+
+        //! Age out old values density to account for \p time passing.
+        virtual void propagateForwardsByTime(double time) = 0;
+
+        //! Debug the memory used by this object.
+        virtual void debugMemoryUsage(core::CMemoryUsage::TMemoryUsagePtr mem) const = 0;
+
+        //! Get the static size of this object.
+        virtual std::size_t staticSize() const = 0;
+
+        //! Get the memory used by this object.
+        virtual std::size_t memoryUsage() const = 0;
+
+        //! Get a checksum for this object.
+        virtual uint64_t checksum(uint64_t seed) const = 0;
+};
+
+//! \brief An implementation of the class conditional density function
+//! based on the CPrior hierarchy.
+class MATHS_EXPORT CNaiveBayesFeatureDensityFromPrior final : public CNaiveBayesFeatureDensity
+{
+    public:
+        CNaiveBayesFeatureDensityFromPrior() = default;
+        CNaiveBayesFeatureDensityFromPrior(CPrior &prior);
+
+        //! Create and return a clone.
+        //!
+        //! \note The caller owns this.
+        virtual CNaiveBayesFeatureDensityFromPrior *clone() const;
+
+        //! Initialize by reading state from \p traverser.
+        virtual bool acceptRestoreTraverser(const SDistributionRestoreParams &params,
+                                            core::CStateRestoreTraverser &traverser);
+
+        //! Persist state by passing information to \p inserter.
+        virtual void acceptPersistInserter(core::CStatePersistInserter &inserter) const;
+
+        //! Add the value \p x.
+        virtual void add(const TDouble1Vec &x);
+
+        //! Compute the log value of the density function at \p x.
+        virtual double logValue(const TDouble1Vec &x) const;
+
+        //! Age out old values density to account for \p time passing.
+        virtual void propagateForwardsByTime(double time);
+
+        //! Debug the memory used by this object.
+        virtual void debugMemoryUsage(core::CMemoryUsage::TMemoryUsagePtr mem) const;
+
+        //! Get the static size of this object.
+        virtual std::size_t staticSize() const;
+
+        //! Get the memory used by this object.
+        virtual std::size_t memoryUsage() const;
+
+        //! Get a checksum for this object.
+        virtual uint64_t checksum(uint64_t seed) const;
+
+    private:
+        using TPriorPtr = boost::shared_ptr<CPrior>;
+
+    private:
+        //! The density model.
+        TPriorPtr m_Prior;
+};
+
+//! \brief Implements a Naive Bayes classifier.
+class MATHS_EXPORT CNaiveBayes
+{
+    public:
+        using TDoubleSizePr = std::pair<double, std::size_t>;
+        using TDoubleSizePrVec = std::vector<TDoubleSizePr>;
+        using TDouble1Vec = core::CSmallVector<double, 1>;
+        using TDouble1VecVec = std::vector<TDouble1Vec>;
+
+    public:
+        explicit CNaiveBayes(const CNaiveBayesFeatureDensity &exemplar,
+                             double decayRate = 0.0);
+        CNaiveBayes(const SDistributionRestoreParams &params,
+                    core::CStateRestoreTraverser &traverser);
+
+        //! Persist state by passing information to \p inserter.
+        void acceptPersistInserter(core::CStatePersistInserter &inserter) const;
+
+        //! This can be used to optionally seed the class counts
+        //! with \p counts. These are added on to data class counts
+        //! to compute the class posterior probabilities.
+        void initialClassCounts(const TDoubleSizePrVec &counts);
+
+        //! Add a training data point comprising the pair \f$(x,l)\f$
+        //! for feature vector \f$x\f$ and class label \f$l\f$.
+        //!
+        //! \param[in] label The class label for \p x.
+        //! \param[in] x The feature values.
+        //! \note \p x size should be equal to the number of features.
+        //! A feature is missing is indicated by passing an empty vector
+        //! for that feature.
+        void addTrainingDataPoint(std::size_t label, const TDouble1VecVec &x);
+
+        //! Age out old values from the class conditional densities
+        //! to account for \p time passing.
+        void propagateForwardsByTime(double time);
+
+        //! Get the top \p n class probabilities for \p features.
+        //!
+        //! \param[in] n The number of class probabilities to estimate.
+        //! \param[in] x The feature values.
+        //! \note \p x size should be equal to the number of features.
+        //! A feature is missing is indicated by passing an empty vector
+        //! for that feature.
+        TDoubleSizePrVec highestClassProbabilities(std::size_t n,
+                                                   const TDouble1VecVec &x) const;
+
+        //! Debug the memory used by this object.
+        void debugMemoryUsage(core::CMemoryUsage::TMemoryUsagePtr mem) const;
+
+        //! Get the memory used by this object.
+        std::size_t memoryUsage() const;
+
+        //! Get a checksum for this object.
+        uint64_t checksum(uint64_t seed = 0) const;
+
+    private:
+        using TFeatureDensityPtr = boost::shared_ptr<CNaiveBayesFeatureDensity>;
+        using TFeatureDensityPtrVec = std::vector<TFeatureDensityPtr>;
+
+        //! \brief The data associated with a class.
+        struct SClass
+        {
+            //! Initialize by reading state from \p traverser.
+            bool acceptRestoreTraverser(const SDistributionRestoreParams &params,
+                                        core::CStateRestoreTraverser &traverser);
+            //! Persist state by passing information to \p inserter.
+            void acceptPersistInserter(core::CStatePersistInserter &inserter) const;
+            //! Debug the memory used by this object.
+            void debugMemoryUsage(core::CMemoryUsage::TMemoryUsagePtr mem) const;
+            //! Get the memory used by this object.
+            std::size_t memoryUsage() const;
+            //! Get a checksum for this object.
+            uint64_t checksum(uint64_t seed = 0) const;
+
+            //! The number of examples in this class.
+            double s_Count = 0.0;
+            //! The feature conditional densities for this class.
+            TFeatureDensityPtrVec s_ConditionalDensities;
+        };
+
+        using TSizeClassUMap = boost::unordered_map<std::size_t, SClass>;
+
+    private:
+        //! Initialize by reading state from \p traverser.
+        bool acceptRestoreTraverser(const SDistributionRestoreParams &params,
+                                    core::CStateRestoreTraverser &traverser);
+
+        //! Validate \p x.
+        bool validate(const TDouble1VecVec &x) const;
+
+    private:
+        //! Controls the rate at which data are aged out.
+        double m_DecayRate;
+
+        //! An exemplar for creating conditional densities.
+        TFeatureDensityPtr m_Exemplar;
+
+        //! The class conditional density estimates and weights.
+        TSizeClassUMap m_ClassConditionalDensities;
+};
+
+}
+}
+
+#endif // INCLUDED_ml_maths_CNaiveBayes_h