1 Fitting classifiers by hand 1. (10 points) Consider two training points: (2) =-2, y(2-1. Derive the Perceptron algorithm step by step until it converges by hand Initialization: step size a 0.2, bias b 1, and w1 The order at which the training points are used: Sample 1, Sample 2, Sample 1, Sample , Sample 1, Sample 1, Sample 1, Sample 2, Sample 2, Sample 1, Sample 2, Sample 1, Sample 2,... (may not necessarily use the entire sequence) Stopping criterion: until all the samples are correctly classified. 1 Fitting classifiers by hand 1. (10 points) Consider two training points: (2) =-2, y(2-1. Derive the Perceptron algorithm step by step until it converges by hand Initialization: step size a 0.2, bias b 1, and w1 The order at which the training points are used: Sample 1, Sample 2, Sample 1, Sample , Sample 1, Sample 1, Sample 1, Sample 2, Sample 2, Sample 1, Sample 2, Sample 1, Sample 2,... (may not necessarily use the entire sequence) Stopping criterion: until all the samples are correctly classified