Results of contrast set learning techniques

Results of contrast set learning techniques 

What was done using different techniques:

1. Cluster jplflight(-->C1) with xy_proj.py -->C2

2. Build decision trees using xy_dt.py

3. Use diff.py to get decisions(contrast sets) to be made for worse cluster to be better cluster.

4. Using the contrast sets generate 500 samples with gen.py. (used xomo)-->C3

5. Compare initial clusters to newly generated data.

6. Represent results as in fig 9 of http://menzies.us/pdf/12gense.pdf .

Techniques:
T0: asIs
T2 =C1+C3 
T3 = C2+C3


Flight data

 Techniques         -effort         -months        -defects          -risks    #
           T0 m              43              74              14               9    #
           T2 m               0               3               0               1    #
           T3 m               0               4               0               0    #
           T0 q              32              17              21              26    #
           T2 q               0               0               1               2    #
           T3 q               0               0               1               2    #
           T0 w             100             100             100             100    #
           T2 w               2               7              25              15    #
           T3 w               2               7              21              13    #
            100         30166.1            88.6         27118.6             1.8    #
              0          9598.8            16.4          4340.4             0.2    #

Ground data

  Techniques         -effort         -months        -defects          -risks    #
           T0 m              43              74              15              10    #
           T2 m               0               3               0               1    #
           T3 m               0               3               0               0    #
           T0 q              32              17              21              27    #
           T2 q               0               0               1               3    #
           T3 q               0               0               1               3    #
           T0 w             100             100             100             100    #
           T2 w               1               7              18              17    #
           T3 w               1               6              16              15    #
            100         30166.1            88.6         27118.6             1.8    #
              0          9598.8            16.4          4340.4             0.2    #

Osp data

 Techniques         -effort         -months        -defects          -risks    #
           T0 m              43              74              12               0    #
           T2 m               0               4               0              12    #
           T3 m               0               4               0              12    #
           T0 q              32              18              19              19    #
           T2 q               0               0               1               9    #
           T3 q               0               0               0               8    #
           T0 w             100             100             100             100    #
           T2 w               1               6              24              33    #
           T3 w               1               6              20              33    #
            100         30166.1            88.6         27118.6             1.8    #
              0          9598.8            16.4          6021.0             0.2    #

Osp2 data

Techniques         -effort         -months        -defects          -risks    #
           T0 m              43              74              14               3    #
           T2 m               0               4               0               0    #
           T3 m               0               4               0               0    #
           T0 q              32              18              21              22    #
           T2 q               0               0               0               2    #
           T3 q               0               0               0               2    #
           T0 w             100             100             100             100    #
           T2 w               1               6              14              14    #
           T3 w               1               6              11              14    #
            100         30166.1            88.6         27118.6             1.8    #
              0          9598.8            16.4          6021.0             0.2    #