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| // current | |
| func (ap *AveragedPerceptron) maxScore(m map[string]float64) string { | |
| var maxKey string | |
| var maxVal float64 = math.SmallestNonzeroFloat64 | |
| for k, _ := range ap.Classes { | |
| v, ok := m[k] | |
| if !ok { | |
| v = 0.0 | |
| } | |
| if v > maxVal || (v == maxVal && strings.Compare(k, maxKey) > 0) { | |
| maxKey = k | |
| maxVal = v | |
| } | |
| } | |
| return maxKey | |
| } | |
| // previous | |
| func (ap *AveragedPerceptron) maxScore(m map[string]float64) string { | |
| var maxKey string | |
| var maxVal float64 | |
| for k, v := range m { | |
| switch { | |
| case v > maxVal: | |
| maxKey = k | |
| maxVal = v | |
| case v == maxVal: | |
| if k < maxKey { | |
| maxKey = k | |
| maxVal = v | |
| } | |
| } | |
| } | |
| return maxKey | |
| } | |
| // _perceptron.py | |
| self.classes = set() | |
| ... | |
| scores = defaultdict(float) | |
| ... | |
| return max(self.classes, key=lambda label: (scores[label], label)) | |
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