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# Bio.LogisticRegression.classify

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```    def test_classify(self):
model = LogisticRegression.train(xs, ys)
result = LogisticRegression.classify(model, [6, -173.143442352])
self.assertEqual(result, 1)
result = LogisticRegression.classify(model, [309, -271.005880394])
```
```        predictions = [1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0]
for i in range(len(predictions)):
prediction = LogisticRegression.classify(model, xs[i])
self.assertEqual(prediction, predictions[i])
if prediction==ys[i]:
```
```        for i in range(len(predictions)):
model = LogisticRegression.train(xs[:i]+xs[i+1:], ys[:i]+ys[i+1:])
prediction = LogisticRegression.classify(model, xs[i])
self.assertEqual(prediction, predictions[i])
if prediction==ys[i]:
```

```    def test_classify(self):
model = LogisticRegression.train(xs, ys)
result = LogisticRegression.classify(model, [6, -173.143442352])
self.assertEqual(result, 1)
result = LogisticRegression.classify(model, [309, -271.005880394])
```
```        predictions = [1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0]
for i in range(len(predictions)):
prediction = LogisticRegression.classify(model, xs[i])
self.assertEqual(prediction, predictions[i])
if prediction==ys[i]:
```
```        for i in range(len(predictions)):
model = LogisticRegression.train(xs[:i]+xs[i+1:], ys[:i]+ys[i+1:])
prediction = LogisticRegression.classify(model, xs[i])
self.assertEqual(prediction, predictions[i])
if prediction==ys[i]:
```