notebook.community

Edit and run



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import sys
print(sys.version)



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from functools import partial
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
from mnist_helpers import mnist_training, mnist_testing



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X_train, y_train = mnist_training()



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data_points = 1000 
X_train, y_train = X_train[0:data_points], y_train[0:data_points]



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model = LeastSquaresSGD(X=X_train, y=y_train, batch_size=100, kernel=RBFKernel,
                        verbose=True,
                        progress_monitoring_freq=2000, max_epochs=50)



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model.eta0



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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_01_loss(logx=True)



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model.plot_square_loss(logx=False)



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model.plot_w_hat_history()



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model.results.columns



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model.plot_loss_and_eta()

Should diverge:



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model_diverge = LeastSquaresSGD(X=X, y=y, batch_size=2, eta0 = model.eta0*10,
                                kernel=RBFKernel, 
                                progress_monitoring_freq=100, max_epochs=500)
model_diverge.run()



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model_diverge.plot_square_loss()