[mlpack-svn] r17278 - mlpack/trunk/src/mlpack/core/dists
fastlab-svn at coffeetalk-1.cc.gatech.edu
fastlab-svn at coffeetalk-1.cc.gatech.edu
Sun Nov 2 12:52:53 EST 2014
Author: michaelfox99
Date: Sun Nov 2 12:52:53 2014
New Revision: 17278
Log:
Rename hmm_regression.hpp
Added:
mlpack/trunk/src/mlpack/core/dists/regression_distribution.hpp
Added: mlpack/trunk/src/mlpack/core/dists/regression_distribution.hpp
==============================================================================
--- (empty file)
+++ mlpack/trunk/src/mlpack/core/dists/regression_distribution.hpp Sun Nov 2 12:52:53 2014
@@ -0,0 +1,102 @@
+/**
+ * @file regression_distribution.hpp
+ * @author Michael Fox
+ *
+ * Implementation of conditional Gaussian distribution for HMM regression (HMMR)
+ */
+#ifndef __MLPACK_METHODS_HMM_DISTRIBUTIONS_REGRESSION_DISTRIBUTION_HPP
+#define __MLPACK_METHODS_HMM_DISTRIBUTIONS_REGRESSION_DISTRIBUTION_HPP
+
+#include <mlpack/core.hpp>
+#include <mlpack/core/dists/gaussian_distribution.hpp>
+#include <mlpack/methods/linear_regression/linear_regression.hpp>
+
+namespace mlpack {
+namespace distribution {
+
+/**
+ * A class that represents a univariate conditionally Gaussian distribution.
+ * Can be used as an emission distribution with the hmm class to implement HMM
+ * regression (HMMR) as described in
+ * https://www.ima.umn.edu/preprints/January1994/1195.pdf
+ * The hmm observations should have the dependent variable in the first row,
+ * with the independent variables in the other rows.
+ */
+class RegressionDistribution
+{
+ private:
+ //! Regression function for representing conditional mean.
+ regression::LinearRegression rf;
+ //! Error distribution
+ GaussianDistribution err;
+
+ public:
+ /**
+ * Default constructor, which creates a Gaussian with zero dimension.
+ */
+ RegressionDistribution() { /* nothing to do */ }
+
+ /**
+ * Create a Conditional Gaussian distribution with conditional mean function
+ * obtained by running RegressionFunction on predictors, responses.
+ *
+ * @param predictors Matrix of predictors (X).
+ * @param responses Vector of responses (y).
+ */
+ RegressionDistribution(const arma::mat& predictors,
+ const arma::vec& responses) :
+ rf(regression::LinearRegression(predictors, responses))
+ {
+ err = GaussianDistribution(1);
+ err.Covariance() = rf.ComputeError(predictors, responses);
+ }
+
+ /**
+ * Returns a string representation of this object.
+ */
+ std::string ToString() const;
+
+ // Return regression function
+ const regression::LinearRegression& Rf() {return rf;}
+
+ /**
+ * Estimate the Gaussian distribution directly from the given observations.
+ *
+ * @param observations List of observations.
+ */
+ void Estimate(const arma::mat& observations);
+
+ /**
+ * Estimate parameters using provided observation weights
+ *
+ * @param weights probability that given observation is from distribution
+ */
+ void Estimate(const arma::mat& observations, const arma::vec& weights);
+
+ /**
+ * Evaluate probability density function of given observation
+ *
+ * @param observation point to evaluate probability at
+ */
+ double Probability(const arma::vec& observation) const;
+
+ /**
+ * Calculate y_i for each data point in points.
+ *
+ * @param points the data points to calculate with.
+ * @param predictions y, will contain calculated values on completion.
+ */
+ void Predict(const arma::mat& points, arma::vec& predictions) const;
+
+ //! Return the parameters (the b vector).
+ const arma::vec& Parameters() const { return rf.Parameters(); }
+
+ //! Return the dimensionality (2) NEED TO FIX THIS
+ static const size_t Dimensionality() { return 2; }
+};
+
+
+}; // namespace distribution
+}; // namespace mlpack
+
+#endif
More information about the mlpack-svn
mailing list