lsvm and knn elm

For training: elm_traing(TrainingData_File, Elm_Type, NumberofHiddenNeurons, ActivationFunction)

OR: [TrainingTime, TrainingAccuracy] = elm_train(TrainingData_File, Elm_Type, NumberofHiddenNeurons, ActivationFunction)



For testing/prediction: elm_predict(TestingData_File)

OR: [TestingTime, TestingAccuracy] = elm_predict(TestingData_File)



After training phase completed, the trained network model will be saved in ‘elm_model.mat’, which can be used for prediction by calling function elm_predict. The prediction output will be saved in ‘elm_output.mat’.-lsvm and knn elm

For training: elm_traing(TrainingData_File, Elm_Type, NumberofHiddenNeurons, ActivationFunction)

OR:　　[TrainingTime, TrainingAccuracy] = elm_train(TrainingData_File, Elm_Type, NumberofHiddenNeurons, ActivationFunction)



For testing/prediction: elm_predict(TestingData_File)

OR:　　[TestingTime, TestingAccuracy] = elm_predict(TestingData_File)



After training phase completed, the trained network model will be saved in ‘elm_model.mat’, which can be used for prediction by calling function elm_predict. The prediction output will be saved in ‘elm_output.mat’.