_PROBLEM CoEPrA-2006_Classification_003

_GROUP_NAME Matt Segall

_GROUP_MEMBERS
Joelle Gola
Olga Obrezanova 
Matt Segall

_ADDRESS
Inpharmatica
127 Cambridge Science Park
Milton Road, Cambridge, CB4 0GD, UK
tel. +44(0)1223 706177
e-mail: o.obrezanova@inpharmatica.co.uk

_MODELING_PROCEDURE
1.Calculated one additional descriptor - Molecular weight. 
(for example, see http://www.expasy.org/tools/protparam.html)

2. Descriptor pre-selection. 
  Descriptors with low standard deviation, low occurence and highly 
  correlated were filtered out. 
  Excluded descriptors
- with standard deviation <  5.0E-04
- with occurence < 0.5%
- with correlation coefficient >= 0.9 (only one of a pair left). 

After filtering 2044 descriptors remained. 
 
3. Modelling technique. 
Decision Tree using C4.5 algorithm.
Gain ratio criterion is used to select descriptors.
Original tree is converted to set of rules. Each rule is
 simplified, that is some irrelevant conditions are deleted
 based on results of statistical tests of contingency tables. 
Whole set of rules is simplified by eliminating unnecessary rules. 

Prediction is done by taking sum of votes from all rules that
 apply weighted by rule's accuracy (Laplace Ratio). 

4. Validation.
Cross-Validation procedure (5 groups) was used to choose
 the best model and to obtain an estimate for the misclassification
 rate on unseen set.

5. Final model and statistics.
 Calibration set: 133 cases, 2044 descriptors.

 Ruleset on calibration set:

Rule 1: 
Desc_00196 >  1.02, 
  Desc_03110 >  1.78, class=1  (27/0) accuracy=0.965517

Rule 2: 
Desc_00196 <= 1.02, 
  Desc_01901 >  -0.22, 
    Desc_03474 >  -0.29, class=-1  (25/0) accuracy=0.962963

Rule 3: 
Desc_00196 <= 1.02, 
  Desc_02950 <= 0.581, 
    Desc_05160 <= 8.249, 
      Desc_00687 >  0.32, class=-1  (20/1) accuracy=0.909091

Rule 4: 
Desc_00753 >  0, 
  Desc_01317 <= 0, class=-1  (6/0) accuracy=0.875

Rule 5: 
Desc_01901 <= -0.22, 
  Desc_02957 >  -0.16, 
    Desc_03688 <= 0, class=1  (15/2) accuracy=0.823529

Rule 6: 
Desc_03110 <= 1.78, 
  Desc_02101 >  0.94, class=-1  (31/8) accuracy=0.727273

Rule 7: 
Desc_00196 <= 1.02, 
  Desc_02950 <= 0.581, class=-1  (72/21) accuracy=0.702703

Rule 8: 
Desc_01317 >  0, class=1  (44/16) accuracy=0.630435

Rule 9: 
Desc_01901 <= -0.22, class=1  (86/32) accuracy=0.625

Rule 10 (default): class=1  (133/66) accuracy=0.503704

 
  Number of misclassified cases=16.  Misclassification error = 12.0301%.
  Confusion matrix:
  Class -1   Class 1    <-- predicted 
  -------    -------   
       61         5     | Class -1
       11        56     | Class 1
  
 Kappa statistic: 0.759548.
 Mutual Information: 0.47846.  
 Estimated misclassification rate on unseen set is 37.66% 
 (obtained by cross-validation).


_PREDICTION
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