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import sys
print(sys.version)


    

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import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
%matplotlib inline
import time

import pandas as pd
import seaborn as sns


    

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import sys
sys.path.append('../code/')


    

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from least_squares_sgd import LeastSquaresSGD

from rbf_kernel import RBFKernel


    

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X = np.array([[1, 0., 0], [0, 0, 1.]])
y = np.array([0, 1])


    

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model = LeastSquaresSGD(X=X, y=y, batch_size=2, kernel=RBFKernel,
                        progress_monitoring_freq=2, max_epochs=200)


    

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model.run()


    

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model.results


    

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model.plot_01_loss()


    

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model.plot_square_loss()


    

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model.plot_w_hat_history()


    

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model.W


    

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model.eta0


    

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# Make this one fail:
model_fail = LeastSquaresSGD(X=X, y=y, batch_size=2, eta0=model.eta*4*10, 
                             kernel = RBFKernel,
                             progress_monitoring_freq=2, max_epochs=200)
model_fail.run()


    

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model_fail.plot_square_loss()


    

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