26 lines
893 B
Mathematica
26 lines
893 B
Mathematica
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% implements KNN, returns the test error for the k-nearest neighbors
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% algorithms when using a specified number of neighbors (k) for
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% classification using a majority rules with tie-breaking.
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function [test_err] = KNN(k, training_data, test_data, training_labels, test_labels)
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n = length(test_data(:,1)); % get number of rows in test data
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preds = zeros(length(test_labels),1); % predict labels for each test point
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% TODO: compute pairwise euclidean distance between the test data and the
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% training data
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% for each data point (row) in the test data
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for t = 1:n
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% TODO: compute k-nearest neighbors for data point
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% TODO: classify test point using majority rule. Include tie-breaking
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% using whichever class is closer by distance. Fill in preds with the
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% predicted label.
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end
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test_err = sum(preds ~= test_labels)/n; % error rate
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end % Function end
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