preamble
Perceptrons are linear classification models for categorization, where the input is the feature vector of the instance and the output is the category of the instance, taking values of +1 or -1 as positive or negative categories. The perceptron corresponds to a hyperplane in the input space that categorizes the input features and is a discriminative model.
The perceptron model is obtained by minimizing the misclassification loss function through gradient descent.
This section describes the specific principle code that implements the Perceptron implementation:.
fate
The line results are shown in Fig:
summarize
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