Implement the perceptron algorithm whose weight update rule is given by
, where n is the learning rate parameter. Train your perceptron using the dataset in file “Data2.txt” for n in the range [0.0007, 0.0017] with a step of 0.0001. Each row in the file represents one input vector. The first 2 columns correspond to the input features (x1 and x2), while the third column corresponds to the target values (t = -1 or t = 1). Start with initial weight vector w(0)=[1 0 0] T.
인용 양식
Shaimaa Omer (2024). Perceptron (https://www.mathworks.com/matlabcentral/fileexchange/134891-perceptron), MATLAB Central File Exchange. 검색됨 .
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