The road to machine learning: python dictionary feature extractor DictVectorizer

 

python3 learn to use api

Extract features from samples of dictionary-type data structures and convert them into vector form

Source code git: https://github.com/linyi0604/MachineLearning

Code:

1  from sklearn.feature_extraction import DictVectorizer
 2  
3  ''' 
4  Dictionary feature extractor:
 5 Extract      and vectorize the dictionary data structure
 6      Category type features are vectorized using 0 1 binary method with the help of prototype feature names
 7      Numeric type features remain unchanged Variable
 8  ''' 
9  
10  #Define a list of dictionaries to represent multiple data samples 
11 measurements = [
 12      { " city " : " Dubai " , " temperature " : 33.0 },
 13      { " city " :" London " , " temperature " : 12.0 },
 14      { " city " : " San Fransisco " , " temperature " : 18.0 },
 15  ]
 16  
17  #Initialize dictionary feature extractor 
18 vec = DictVectorizer()
 19 data = vec. fit_transform(measurements).toarray()
 20  #View the extracted feature values 
​​21  print (data)
 22  ''' 
23  [[ 1. 0. 0. 33.]
 24 [ 0. 1. 0. 12.]
 25  [ 0. 0. 1. 18.]]
 26  ''' 
27  #View the meaning of the extracted features 
28  print (vec.get_feature_names())
 29  ''' 
30  [' city=Dubai', 'city=London', 'city=San Fransisco', 'temperature']
 31  '''