Analytics: minor fix to the Regressor and Classifier plugins

analytics/operators/regressor/RegressorOperator.cpp

@@ -199,12 +199,13 @@ void RegressorOperator::computeFeatureVector(U_Ptr unit) {
     uint64_t startTs = endTs - _aggregationWindow;
     std::vector<RegressorSBPtr>& inputs = unit->getInputs();
     for(idx=0; idx<inputs.size(); idx++) {
-        _mean=0; _std=0; _diffsum=0; _qtl25=0; _qtl75=0;
+        _mean=0; _std=0; _diffsum=0; _qtl25=0; _qtl75=0; _latest=0;
         _buffer.clear();
         if(!_queryEngine.querySensor(inputs[idx]->getName(), startTs, endTs, _buffer, false) || _buffer.empty())
             throw std::runtime_error("Operator " + _name + ": cannot read from sensor " + inputs[idx]->getName() + "!");
+        _latest = _buffer.back().value;
         if (inputs[idx]->getTrainingTarget())
-            _currentTarget = (float)_buffer.back().value;
+            _currentTarget = (float)_latest;
 
         if(!inputs[idx]->getTrainingTarget() || _includeTarget) {
             // Computing MEAN and SUM OF DIFFERENCES
@@ -245,7 +246,7 @@ void RegressorOperator::computeFeatureVector(U_Ptr unit) {
             _currentfVector->at<float>(fIdx + 2) = (float) _diffsum;
             _currentfVector->at<float>(fIdx + 3) = (float) _qtl25;
             _currentfVector->at<float>(fIdx + 4) = (float) _qtl75;
-            _currentfVector->at<float>(fIdx + 5) = (float) _buffer[_buffer.size() - 1].value;
+            _currentfVector->at<float>(fIdx + 5) = (float) _latest;
         } else {
             fIdx = idx * REG_NUMFEATURES;
             _currentfVector->at<float>(fIdx) = 0.0f;

analytics/operators/regressor/RegressorOperator.h

@@ -103,6 +103,7 @@ protected:
     int64_t _diffsum;
     int64_t _qtl25;
     int64_t _qtl75;
+    int64_t _latest;
 
     // Helper struct to store importance pairs
     struct ImportancePair {