Brain Computer Interface P300 Machine Learning - c++

Question

I am currently working a P300 (basically there is detectable increase in a brain wave when a user sees something they are interested) detection system in C++ using the Emotiv EPOC. The system works but to improve accuracy I'm attempting to use Wekinator for machine learning, using an support vector machine (SVM).
So for my P300 system I have three stimuli (left, right and forward arrows). My program keeps track of the stimulus index and performs some filtering on the incoming "brain wave" and then calculates which index has the highest average area under the curve to determine which stimuli the user is looking at.
For my integration with Wekinator: I have setup Wekinator to receive a custom OSC message with 64 features (the length of the brain wave related to the P300) and set up three parameters with discrete values of 1 or 0. For training I have I have been sending the "brain wave" for each stimulus index in a trial and setting the relevant parameters to 0 or 1, then training it and running it. The issue is that when the OSC message is received by the the program from Wekinator it is returning 4 messages, rather than just the one most likely.
Here is the code for the training (and input to Wekinator during run time):
for(int s=0; s < stimCount; s++){
for(int i=0; i < stimIndexes[s].size(); i++) {
int eegIdx = stimIndexes[s][i];
ofxOscMessage wek;
wek.setAddress("/oscCustomFeatures");
if (eegIdx + winStart + winLen < sig.size()) {
int winIdx = 0;
for(int e=eegIdx + winStart; e < eegIdx + winStart + winLen; e++) {
wek.addFloatArg(sig[e]);
//stimAvgWins[s][winIdx++] += sig[e];
}
validWindowCount[s]++;
}
std::cout << "Num args: " << wek.getNumArgs() << std::endl;
wekinator.sendMessage(wek);
}
}
Here is the receipt of messages from Wekinator:
if(receiver.hasWaitingMessages()){
ofxOscMessage msg;
while(receiver.getNextMessage(&msg)) {
std::cout << "Wek Args: " << msg.getNumArgs() << std::endl;
if (msg.getAddress() == "/OSCSynth/params"){
resultReceived = true;
if(msg.getArgAsFloat(0) == 1){
result = 0;
} else if(msg.getArgAsFloat(1) == 1){
result = 1;
} else if(msg.getArgAsFloat(2) == 1){
result = 2;
}
std::cout << "Wek Result: " << result << std::endl;
}
}
}
Full code for both is at the following Gist:
https://gist.github.com/cilliand/f716c92933a28b0bcfa4
Main query is basically whether something is wrong with the code: Should I send the full "brain wave" for a trial to Wekinator? Or should I train Wekinator on different features? Does the code look right or should it be amended? Is there a way to only receive one OSC message back from Wekinator based on smaller feature sizes i.e. 64 rather than 4 x 64 per stimulus or 9 x 64 per stimulus index.