Created
October 7, 2019 21:31
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Three iterations of updates for perceptron weights
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weights = initialize_weights(train_data.shape[1]) | |
for epoch in range(3): | |
sum_of_squared_errors = 0.0 | |
for sample in range(train_data.shape[0]): | |
vector = train_data.loc[sample].values | |
label = train_label.loc[sample] | |
prediction = predict(vector, weights, 'step') | |
error = label - prediction | |
sum_of_squared_errors += error**2 | |
weights = weights + error * vector | |
print(f'SSE: {sum_of_squared_errors}') | |
print(f'Weights: {weights}') |
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