文件名称:lsvm-and-knn-elm
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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’.
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’.
(系统自动生成,下载前可以参看下载内容)
下载文件列表
lsvm.m
KNN.pdf