[Python书籍]Building Machine Learning Systems with Python - Second Edition

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谢谢分享~

1. import numpy as np
   
2. def learn_model(k, features, labels):
   
3.     return k, features.copy(),labels.copy()
   
4. 
   
5. def plurality(xs):
   
6.     from collections import defaultdict
   
7.     counts = defaultdict(int)
   
8.     for x in xs:
   
9.         counts[x] += 1
   
10.     maxv = max(counts.values())
    
11.     for k,v in counts.items():
    
12.         if v == maxv:
    
13.             return k
    
14. 
    
15. def apply_model(features, model):
    
16.     k, train_feats, labels = model
    
17.     results = []
    
18.     for f in features:
    
19.         label_dist = []
    
20.         for t,ell in zip(train_feats, labels):
    
21.             label_dist.append( (np.linalg.norm(f-t), ell) )
    
22.         label_dist.sort(key=lambda d_ell: d_ell[0])
    
23.         label_dist = label_dist[:k]
    
24.         results.append(plurality([ell for _,ell in label_dist]))
    
25.     return np.array(results)
    
26. 
    
27. def accuracy(features, labels, model):
    
28.     preds = apply_model(features, model)
    
29.     return np.mean(preds == labels)

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感谢分享， 可以好好学习一下