Added GLM

src/shogun/regression/GLM.cpp

@@ -0,0 +1,38 @@
+#include <shogun/lib/config.h>
+
+#include <shogun/labels/RegressionLabels.h>
+#include <shogun/mathematics/Math.h>
+#include <shogun/mathematics/linalg/LinalgNamespace.h>
+#include <shogun/regression/GLM.h>
+#include <utility>
+using namespace shogun;
+
+GLM::GLM() : LinearMachine()
+{
+	init();
+}
+
+void GLM::init()
+{
+	SG_ADD(&m_alpha, "alpha", "alpha parameter", ParameterProperties::HYPER);
+	SG_ADD(&m_lambda, "lambda", "lambda parameter", ParameterProperties::HYPER);
+	SG_ADD(
+	    (std::shared_ptr<SGObject>*)&m_descend_updater, "descend_updater",
+	    "Descend Updater used for updating weights",
+	    ParameterProperties::SETTING);
+	SG_ADD(&m_family, "family", "family used", ParameterProperties::SETTING);
+	SG_ADD(
+	    &m_linkfn, "linkfn", "Link function used",
+	    ParameterProperties::SETTING);
+}
+GLM::GLM(
+    std::shared_ptr<DescendUpdater> descend_updater, Family family,
+    LinkFunction Link_fn, float64_t alpha, float64_t lambda)
+    : LinearMachine()
+{
+	m_alpha = alpha;
+	m_lambda = lambda;
+	m_linkfn = Link_fn;
+	m_descend_updater = descend_updater;
+	m_family = family;
+}

src/shogun/regression/GLM.h

@@ -0,0 +1,112 @@
+/*
+ * This software is distributed under BSD 3-clause license (see LICENSE file).
+ *
+ * Authors: Ahmed Khalifa
+ */
+/*
+References:
+https://www.rdocumentation.org/packages/stats/versions/3.6.2/topics/family
+https://www.statsmodels.org/stable/generated/statsmodels.genmod.generalized_linear_model.GLM.html#statsmodels.genmod.generalized_linear_model.GLM
+http://glm-tools.github.io/pyglmnet/api.html
+*/
+#ifndef _GENERALIZEDLINEARMODEL_H__
+#define _GENERALIZEDLINEARMODEL_H__
+
+#include <shogun/lib/config.h>
+
+#include <shogun/features/Features.h>
+#include <shogun/machine/FeatureDispatchCRTP.h>
+#include <shogun/machine/LinearMachine.h>
+#include <shogun/optimization/DescendUpdater.h>
+#include <shogun/regression/Regression.h>
+
+namespace shogun
+{
+	enum Family
+	{
+		NORMAL_DISTRIBUTION,
+		EXPONENTIAL_DISTRIBUTION,
+		GAMMA_DISTRIBUTION,
+		BINOMIAL_DISTRIBUTION,
+		GAUSS_DISTRIBUTION,
+		POISSON_DISTRIBUTION
+	};
+	enum LinkFunction
+	{
+		LOG,
+		LOGIT,
+		IDENTITY,
+		INVERSE
+	};
+	/** @brief Class GLM implements Generalized Linear Models, such as poisson,
+	 * gamma, binomial
+	 */
+	class GLM : public LinearMachine
+	{
+	public:
+		/** problem type */
+		MACHINE_PROBLEM_TYPE(PT_REGRESSION);
+
+		/** Default constructor */
+		GLM();
+
+		/** Constructor
+		 *
+		 * @param descend_updater chosen Descend Updater algorithm
+		 * @param Linkfn the link function check
+		 * https://www.rdocumentation.org/packages/stats/versions/3.6.2/topics/family
+		 * @param Family the family check
+		 * https://www.rdocumentation.org/packages/stats/versions/3.6.2/topics/family
+		 * @param alpha alpha
+		 * @param lambda lambda
+		 */
+		GLM(std::shared_ptr<DescendUpdater>,
+		    Family family = POISSON_DISTRIBUTION, LinkFunction Link_fn = LOG,
+		    float64_t alpha = 0.5, float64_t lambda = 0.1);
+
+		/** standard constructor
+		 * @param data features
+		 * @param labs labels
+		 * @param learn_rate Learning rate
+		 * @param Linkfn the link function check
+		 * https://www.rdocumentation.org/packages/stats/versions/3.6.2/topics/family
+		 * @param Family the distribution/family check
+		 * https://www.rdocumentation.org/packages/stats/versions/3.6.2/topics/family
+		 * @param alpha alpha
+		 * @param lambda lambda
+		 */
+
+		/** default destructor */
+		virtual ~GLM()
+		{
+		}
+
+		/** train model
+		 *
+		 * @param data training data
+		 *
+		 * @return whether training was successful
+		 */
+		virtual bool train_machine(std::shared_ptr<Features> data = NULL)
+		{
+			return true;
+		};
+
+		/** @return object name */
+		virtual const char* get_name() const
+		{
+			return "GLM";
+		}
+
+	protected:
+		std::shared_ptr<DescendUpdater> m_descend_updater;
+		float64_t m_alpha;
+		float64_t m_lambda;
+		Family m_family;
+		LinkFunction m_linkfn;
+
+	private:
+		void init();
+	};
+} // namespace shogun
+#endif /* _GLM_H_ */