Added MLPPDataOld.

SCsub

@@ -83,6 +83,7 @@ sources = [
     "mlpp/stat/stat_old.cpp",
     "mlpp/lin_alg/lin_alg_old.cpp",
     "mlpp/hypothesis_testing/hypothesis_testing_old.cpp",
+    "mlpp/data/data_old.cpp",
 
     "test/mlpp_tests.cpp",
 ]

mlpp/data/data_old.h

@@ -0,0 +1,201 @@
+
+#ifndef MLPP_DATA_OLD_H
+#define MLPP_DATA_OLD_H
+
+//
+//  Data.hpp
+//  MLP
+//
+//  Created by Marc Melikyan on 11/4/20.
+//
+
+#include "core/math/math_defs.h"
+
+#include "core/string/ustring.h"
+#include "core/variant/array.h"
+
+#include "core/object/reference.h"
+
+#include "../lin_alg/mlpp_matrix.h"
+#include "../lin_alg/mlpp_vector.h"
+
+#include <string>
+#include <tuple>
+#include <vector>
+
+class MLPPDataOldESimple : public Reference {
+	GDCLASS(MLPPDataOldESimple, Reference);
+
+public:
+	Ref<MLPPVector> get_input();
+	void set_input(const Ref<MLPPVector> &val);
+
+	Ref<MLPPVector> get_output();
+	void set_output(const Ref<MLPPVector> &val);
+
+	void instance_data();
+
+protected:
+	static void _bind_methods();
+
+	Ref<MLPPVector> _input;
+	Ref<MLPPVector> _output;
+};
+
+class MLPPDataOldSimple : public Reference {
+	GDCLASS(MLPPDataOldSimple, Reference);
+
+public:
+	Ref<MLPPMatrix> get_input();
+	void set_input(const Ref<MLPPMatrix> &val);
+
+	Ref<MLPPVector> get_output();
+	void set_output(const Ref<MLPPVector> &val);
+
+	void instance_data();
+
+protected:
+	static void _bind_methods();
+
+	Ref<MLPPMatrix> _input;
+	Ref<MLPPVector> _output;
+};
+
+class MLPPDataOldComplex : public Reference {
+	GDCLASS(MLPPDataOldComplex, Reference);
+
+public:
+	Ref<MLPPMatrix> get_input();
+	void set_input(const Ref<MLPPMatrix> &val);
+
+	Ref<MLPPMatrix> get_output();
+	void set_output(const Ref<MLPPMatrix> &val);
+
+	void instance_data();
+
+protected:
+	static void _bind_methods();
+
+	Ref<MLPPMatrix> _input;
+	Ref<MLPPMatrix> _output;
+};
+
+class MLPPDataOld : public Reference {
+	GDCLASS(MLPPDataOld, Reference);
+
+public:
+	// Load Datasets
+	Ref<MLPPDataOldSimple> load_breast_cancer(const String &path);
+	Ref<MLPPDataOldSimple> load_breast_cancer_svc(const String &path);
+	Ref<MLPPDataOldComplex> load_iris(const String &path);
+	Ref<MLPPDataOldComplex> load_wine(const String &path);
+	Ref<MLPPDataOldComplex> load_mnist_train(const String &path);
+	Ref<MLPPDataOldComplex> load_mnist_test(const String &path);
+	Ref<MLPPDataOldSimple> load_california_housing(const String &path);
+	Ref<MLPPDataOldESimple> load_fires_and_crime(const String &path);
+
+	void set_data_supervised(int k, const String &file_name, Ref<MLPPMatrix> input_set, Ref<MLPPVector> output_set);
+	void set_data_unsupervised(int k, const String &file_name, Ref<MLPPMatrix> input_set);
+	void set_data_simple(const String &file_name, Ref<MLPPVector> input_set, Ref<MLPPVector> output_set);
+
+	struct SplitComplexData {
+		Ref<MLPPDataOldComplex> train;
+		Ref<MLPPDataOldComplex> test;
+	};
+
+	SplitComplexData train_test_split(Ref<MLPPDataOldComplex> data, real_t test_size);
+	Array train_test_split_bind(const Ref<MLPPDataOldComplex> &data, real_t test_size);
+
+	// Load Datasets
+	std::tuple<std::vector<std::vector<real_t>>, std::vector<real_t>> loadBreastCancer();
+	std::tuple<std::vector<std::vector<real_t>>, std::vector<real_t>> loadBreastCancerSVC();
+	std::tuple<std::vector<std::vector<real_t>>, std::vector<std::vector<real_t>>> loadIris();
+	std::tuple<std::vector<std::vector<real_t>>, std::vector<std::vector<real_t>>> loadWine();
+	std::tuple<std::vector<std::vector<real_t>>, std::vector<std::vector<real_t>>> loadMnistTrain();
+	std::tuple<std::vector<std::vector<real_t>>, std::vector<std::vector<real_t>>> loadMnistTest();
+	std::tuple<std::vector<std::vector<real_t>>, std::vector<real_t>> loadCaliforniaHousing();
+	std::tuple<std::vector<real_t>, std::vector<real_t>> loadFiresAndCrime();
+
+	std::tuple<std::vector<std::vector<real_t>>, std::vector<std::vector<real_t>>, std::vector<std::vector<real_t>>, std::vector<std::vector<real_t>>> trainTestSplit(std::vector<std::vector<real_t>> inputSet, std::vector<std::vector<real_t>> outputSet, real_t testSize);
+
+	// Supervised
+	void setData(int k, std::string fileName, std::vector<std::vector<real_t>> &inputSet, std::vector<real_t> &outputSet);
+	void printData(std::vector<std::string> inputName, std::string outputName, std::vector<std::vector<real_t>> inputSet, std::vector<real_t> outputSet);
+
+	// Unsupervised
+	void setData(int k, std::string fileName, std::vector<std::vector<real_t>> &inputSet);
+	void printData(std::vector<std::string> inputName, std::vector<std::vector<real_t>> inputSet);
+
+	// Simple
+	void setData(std::string fileName, std::vector<real_t> &inputSet, std::vector<real_t> &outputSet);
+	void printData(std::string &inputName, std::string &outputName, std::vector<real_t> &inputSet, std::vector<real_t> &outputSet);
+
+	// Images
+	std::vector<std::vector<real_t>> rgb2gray(std::vector<std::vector<std::vector<real_t>>> input);
+	std::vector<std::vector<std::vector<real_t>>> rgb2ycbcr(std::vector<std::vector<std::vector<real_t>>> input);
+	std::vector<std::vector<std::vector<real_t>>> rgb2hsv(std::vector<std::vector<std::vector<real_t>>> input);
+	std::vector<std::vector<std::vector<real_t>>> rgb2xyz(std::vector<std::vector<std::vector<real_t>>> input);
+	std::vector<std::vector<std::vector<real_t>>> xyz2rgb(std::vector<std::vector<std::vector<real_t>>> input);
+
+	// Text-Based & NLP
+	std::string toLower(std::string text);
+	std::vector<char> split(std::string text);
+	std::vector<std::string> splitSentences(std::string data);
+	std::vector<std::string> removeSpaces(std::vector<std::string> data);
+	std::vector<std::string> removeNullByte(std::vector<std::string> data);
+	std::vector<std::string> segment(std::string text);
+	std::vector<real_t> tokenize(std::string text);
+	std::vector<std::string> removeStopWords(std::string text);
+	std::vector<std::string> removeStopWords(std::vector<std::string> segmented_data);
+
+	std::string stemming(std::string text);
+
+	std::vector<std::vector<real_t>> BOW(std::vector<std::string> sentences, std::string = "Default");
+	std::vector<std::vector<real_t>> TFIDF(std::vector<std::string> sentences);
+
+	std::tuple<std::vector<std::vector<real_t>>, std::vector<std::string>> word2Vec(std::vector<std::string> sentences, std::string type, int windowSize, int dimension, real_t learning_rate, int max_epoch);
+
+	struct WordsToVecResult {
+		std::vector<std::vector<real_t>> word_embeddings;
+		std::vector<std::string> word_list;
+	};
+
+	WordsToVecResult word_to_vec(std::vector<std::string> sentences, std::string type, int windowSize, int dimension, real_t learning_rate, int max_epoch);
+
+	std::vector<std::vector<real_t>> LSA(std::vector<std::string> sentences, int dim);
+
+	std::vector<std::string> createWordList(std::vector<std::string> sentences);
+
+	// Extra
+	void setInputNames(std::string fileName, std::vector<std::string> &inputNames);
+	std::vector<std::vector<real_t>> featureScaling(std::vector<std::vector<real_t>> X);
+	std::vector<std::vector<real_t>> meanNormalization(std::vector<std::vector<real_t>> X);
+	std::vector<std::vector<real_t>> meanCentering(std::vector<std::vector<real_t>> X);
+	std::vector<std::vector<real_t>> oneHotRep(std::vector<real_t> tempOutputSet, int n_class);
+	std::vector<real_t> reverseOneHot(std::vector<std::vector<real_t>> tempOutputSet);
+
+	Ref<MLPPMatrix> mean_centering(const Ref<MLPPMatrix> &X);
+	Ref<MLPPMatrix> one_hot_rep(const Ref<MLPPVector> &temp_output_set, int n_class);
+
+	template <class T>
+	std::vector<T> vecToSet(std::vector<T> inputSet) {
+		std::vector<T> setInputSet;
+		for (uint32_t i = 0; i < inputSet.size(); i++) {
+			bool new_element = true;
+			for (uint32_t j = 0; j < setInputSet.size(); j++) {
+				if (setInputSet[j] == inputSet[i]) {
+					new_element = false;
+				}
+			}
+			if (new_element) {
+				setInputSet.push_back(inputSet[i]);
+			}
+		}
+		return setInputSet;
+	}
+
+protected:
+	static void _bind_methods();
+};
+
+#endif /* Data_hpp */