# Commits

committed 52f0bb5

Solved parts 1 & 2 of exercise 8 (anomaly detection)

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• Parent commits 0e0f7d1

# exercise-8/octave/estimateGaussian.m

` %               should contain variance of the i-th feature.`
` %`
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`+mu = sum(X)/size(X,1);`
`+sigma2 = sum((X - repmat(mu,size(X,1),1)) .^2) / size(X,1)`
` % =============================================================`
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# exercise-8/octave/selectThreshold.m

`     %               `
`     % Note: You can use predictions = (pval < epsilon) to get a binary vector`
`     %       of 0's and 1's of the outlier predictions`
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`+    pred = pval < epsilon;;`
`+    tp = sum((pred == 1) & (yval == 1));`
`+    fp = sum((pred == 1) & (yval == 0));`
`+    fn = sum((pred == 0) & (yval == 1));`
`+    prec = tp / (tp + fp);`
`+    rec = tp / (tp + fn);`
`+    f1 = 2 * prec * rec / (prec + rec);`
`+    if (f1 > bestF1)`
`+        bestF1 = f1;`
`+	bestEpsilon = epsilon;`
`+    endif`
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