Source Code for Module rdkit.ML.KNN.KNNRegressionModel

 1  # $Id: KNNRegressionModel.py 997 2009-02-25 06:12:43Z glandrum $ 
 2  # 
 3  #  Copyright (C) 2003 Rational Discovery LLC 
 4  #      All Rights Reserved 
 5  # 
 6   
 7  """ Define the class _KNNRegressionModel_, used to represent a k-nearest neighbhors 
 8  regression model 
 9   
10      Inherits from _KNNModel_ 
11  """ 
12   
13  from rdkit.ML.KNN import KNNModel 
14  from rdkit.ML.KNN import DistFunctions 
15  import math 
16   
17   
18 -class KNNRegressionModel(KNNModel.KNNModel) : 
19    """ This is used to represent a k-nearest neighbor classifier 
20   
21    """ 
22   
23 -  def __init__(self, k, attrs, dfunc) : 
24      self._setup(k, attrs, dfunc) 
25   
26      self._badExamples = [] # list of examples incorrectly classified 
27   
28 -  def type(self): 
29      return "Regression Model" 
30   
31 -  def SetBadExamples(self, examples) : 
32      self._badExamples = examples 
33   
34 -  def GetBadExamples(self) : 
35      return self._badExamples 
36   
37 -  def NameModel(self, varNames) : 
38      self.SetName(self.type()) 
39   
40 -  def PredictExample(self, example, appendExamples=0, weightedAverage=0) : 
41      """ Generates a prediction for an example by looking at its closest neighbors 
42   
43      **Arguments** 
44   
45        - examples: the example to be classified 
46   
47        - appendExamples: if this is nonzero then the example will be stored on this model 
48   
49      **Returns** 
50   
51        - the classification of _example_ 
52   
53      """ 
54      if appendExamples: 
55        self._examples.append(example) 
56   
57      # first find the k-closest examples in the traning set 
58      knnLst = self.GetNeighbors(example) 
59   
60      accum = 0.0 
61      for knn in knnLst: 
62        if not weightedAverage: 
63          accum += knn[1][-1] 
64      if not weightedAverage: 
65        accum /= len(knnLst) 
66   
67      return accum 
68