###########Disambiguation-Free Partial Label Learning###########

NOTES: 
a) Libsvm is utilized as the binary learning algorithm to instantiate PL-ECOC (under the "tool" directory after unzipping the PL-ECOC code pacakge)
b) Type "help PLECOC_train" and "help PLECOC_predict" for detailed information on how to use the training and prediction procedures

**running example**

	dataset={'sample data'}; % Load sample data
	str='-t 2 -c 1'; % Set parameters for base Libsvm classifiers used by PL-ECOC at your own choice
	for filename=dataset
		load([filename{1} '.mat']);
		CodewordLength = int32(40*log2(size(train_p_target,1))); % Set codeword length at your own choice
		model = PLECOC_train(train_data,train_p_target,CodewordLength,0.1*size(train_data,1),str); % Train PL-ECOC classifiers
		[accuarcy,~,~] = PLECOC_predict(test_data,test_target,model,1); % Predict with loss weighted decoding
	end