fixing references to default phrase in XMM

src/machineLearning/machineLearning.cpp

@@ -56,6 +56,12 @@ bool machineLearning<seriesClassification>::train(const trainingData &newTrainin
     return seriesClassification::trainLabel(seriesSet);
 }
 
+///Generic train
+template <class MachineLearningModule>
+bool machineLearning<MachineLearningModule>::train(const trainingData &newTrainingData) {
+    return MachineLearningModule::train(newTrainingData);
+}
+
 template<>
 std::string machineLearning<classification>::run(const std::vector<double> &inputVector, const std::string &label) {
     int classIndex = classification::run(inputVector)[0];

src/machineLearning/rapidXMM/rapidXMM.cpp

@@ -3,17 +3,16 @@
 #include "machineLearning.h"
 
 static bool trainingData2xmmTrainingSet(const rapidmix::trainingData& data, xmm::TrainingSet& set) {
-  if (data.trainingSet.size() <= 1) {
-    // no recorded phrase (only default one)
+  if (data.trainingSet.size() < 1) {
     return false;
   }
 
-  if (data.trainingSet.size() > 1 && data.trainingSet[1].elements.size() == 0) {
+  if (data.trainingSet.size() > 0 && data.trainingSet[0].elements.size() == 0) {
     // empty recorded phrase
     return false;
   }
 
-  rapidmix::trainingData::element el = data.trainingSet[1].elements[0];
+  rapidmix::trainingData::element el = data.trainingSet[0].elements[0];
   int dimIn = static_cast<int>(el.input.size());
   int dimOut = static_cast<int>(el.output.size());
 
@@ -43,9 +42,7 @@ static bool trainingData2xmmTrainingSet(const rapidmix::trainingData& data, xmm:
   set.clear();
 
   //for (auto &phrase : data.trainingSet) {
-  // changed to look starting from index 1
-  // because phrase at index 0 is for unordered elements
-  for (int i = 1; i < data.trainingSet.size(); ++i) {
+  for (int i = 0; i < data.trainingSet.size(); ++i) {
     const rapidmix::trainingData::phrase &phrase = data.trainingSet[i];
     xp.clear();
     xp.label.set(phrase.label);
@@ -193,6 +190,8 @@ std::vector<double> rapidXmmHmr::run(const std::vector<double>& inputVector) {
 ///// generic train method and forward declaration of specialized templates 
 ///////////////////////////////////////////////////////////////////////////
 
+//I wonder why this can't be defined in machineLearning.cpp? -MZ
+
 template <class MachineLearningModule>
 bool rapidmix::machineLearning<MachineLearningModule>::train(const trainingData &newTrainingData) {
     return MachineLearningModule::train(newTrainingData);