###DATA SET
training dataset: ant-1.3, 1.4, 1.5 1.6
test dataset: ant-1.7
The data set can be downloaded at here ###DTREE
mfa=(0, 0.225) :568 #21
|..rfc=(0, 0) :288 #2
|..|..loc=(0, 3) :216 #1 50% * 4 leaf #0 score:0.0
|..|..loc=(10, 125) :288 #1 75% * 4 leaf #1 score:0.0
|..rfc=(1, 1) :856 #1 30% * 26 leaf #2 score:0.0
|..rfc=(2, 3) :560 #2
|..|..wmc=(1, 2) :560 #1 55% * 9 leaf #3 score:0.0
|..|..wmc=(3, 5) :784 #1 40% * 10 leaf #4 score:0.0
|..rfc=(4, 19) :568 #11
|..|..lcom3=(0, 0.96476834) :992 #5
|..|..|..wmc=(3, 5) :992 #2
|..|..|..|..loc=(10, 125) :992 #1 13% * 52 leaf #5 score:0.0
|..|..|..|..loc=(126, 4244) :696 #1 37% * 8 leaf #6 score:0.0
|..|..|..wmc=(6, 100) :520 #3
|..|..|..|..loc=(10, 125) :328 #1 15% * 32 leaf #7 score:0.0
|..|..|..|..loc=(126, 4244) :184 #1 37% * 8 leaf #8 score:0.0
|..|..lcom3=(0.965517241, 1.5) :496 #1 50% * 4 leaf #9 score:0.0
|..|..lcom3=(2, 2) :864 #4
|..|..|..loc=(4, 7) :984 #2
|..|..|..|..wmc=(3, 5) :792 #1 35% * 14 leaf #10 score:0.0
|..|..|..|..wmc=(6, 100) :984 #1 50% * 8 leaf #11 score:0.0
|..|..|..loc=(126, 4244) :488 #1 100% * 4 leaf #12 score:0.0
|..rfc=(20, 247) :144 #7
|..|..wmc=(1, 2) :624 #1 80% * 5 leaf #13 score:0.0
|..|..wmc=(3, 5) :696 #2
|..|..|..lcom3=(0, 0.96476834) :696 #1 41% * 12 leaf #14 score:0.0
|..|..|..lcom3=(2, 2) :560 #1 50% * 4 leaf #15 score:0.5
|..|..wmc=(6, 100) :144 #4
|..|..|..lcom3=(0, 0.96476834) :144 #3
|..|..|..|..loc=(10, 125) :592 #1 28% * 7 leaf #16 score:2.0
|..|..|..|..loc=(126, 4244) :928 #1 6% * 122 leaf #17 score:1.5
|..|..|..lcom3=(0.965517241, 1.5) :432 #1 25% * 12 leaf #18 score:0.0
mfa=(0.236842105, 0.846153846) :832 #4
|..dit=(1, 2) :536 #2
|..|..wmc=(3, 5) :448 #1 22% * 31 leaf #19 score:0.0
|..|..wmc=(6, 100) :536 #1 21% * 33 leaf #20 score:1.0
|..dit=(3, 7) :832 #2
|..|..rfc=(4, 19) :104 #1 40% * 5 leaf #21 score:0.0
|..|..rfc=(20, 247) :832 #1 6% * 218 leaf #22 score:1.0
mfa=(0.847826087, 1) :936 #19
|..wmc=(1, 2) :408 #5
|..|..dit=(1, 2) :432 #2
|..|..|..loc=(10, 125) :432 #1 36% * 19 leaf #23 score:0.0
|..|..|..loc=(126, 4244) :856 #1 83% * 6 leaf #24 score:0.0
|..|..dit=(3, 7) :408 #3
|..|..|..rfc=(2, 3) :408 #1 57% * 14 leaf #25 score:0.0
|..|..|..rfc=(4, 19) :784 #2
|..|..|..|..lcom3=(0, 0.96476834) :160 #1 50% * 4 leaf #26 score:0.0
|..|..|..|..lcom3=(2, 2) :784 #1 31% * 22 leaf #27 score:0.5
|..wmc=(3, 5) :24 #10
|..|..lcom3=(0, 0.96476834) :24 #4
|..|..|..loc=(10, 125) :24 #2
|..|..|..|..rfc=(4, 19) :736 #1 11% * 44 leaf #28 score:0.0
|..|..|..|..rfc=(20, 247) :24 #1 33% * 6 leaf #29 score:1.0
|..|..|..loc=(126, 4244) :800 #2
|..|..|..|..rfc=(4, 19) :800 #1 57% * 7 leaf #30 score:0.0
|..|..|..|..rfc=(20, 247) :512 #1 16% * 12 leaf #31 score:0.0
|..|..lcom3=(0.965517241, 1.5) :920 #3
|..|..|..dit=(1, 2) :920 #2
|..|..|..|..rfc=(4, 19) :992 #1 50% * 6 leaf #32 score:0.5
|..|..|..|..rfc=(20, 247) :920 #1 66% * 9 leaf #33 score:1.0
|..|..|..dit=(3, 7) :584 #1 80% * 5 leaf #34 score:0.0
|..|..lcom3=(2, 2) :696 #3
|..|..|..rfc=(4, 19) :984 #1 40% * 15 leaf #35 score:0.0
|..|..|..rfc=(20, 247) :696 #2
|..|..|..|..dit=(1, 2) :48 #1 40% * 5 leaf #36 score:0.0
|..|..|..|..dit=(3, 7) :696 #1 75% * 4 leaf #37 score:0.5
|..wmc=(6, 100) :936 #4
|..|..rfc=(4, 19) :96 #2
|..|..|..dit=(3, 7) :96 #2
|..|..|..|..loc=(10, 125) :96 #1 45% * 11 leaf #38 score:0.0
|..|..|..|..loc=(126, 4244) :656 #1 25% * 4 leaf #39 score:0.0
|..|..rfc=(20, 247) :936 #2
|..|..|..loc=(10, 125) :344 #1 33% * 6 leaf #40 score:0.0
|..|..|..loc=(126, 4244) :936 #1 17% * 78 leaf #41 score:0.5
###CONSTRAST SET
leaf #15 score:0.5 ==>lcom3=(0, 0.96476834) ==>targetscore=0.0 ==>targeleaf=14
leaf #16 score:2.0 ==>loc=(126, 4244) ==>targetscore=1.5 ==>targeleaf=17
leaf #17 score:1.5 ==>lcom3=(0.965517241, 1.5) ==>targetscore=0.0 ==>targeleaf=18
leaf #20 score:1.0 ==>wmc=(3, 5) ==>targetscore=0.0 ==>targeleaf=19
leaf #22 score:1.0 ==>rfc=(4, 19) ==>targetscore=0.0 ==>targeleaf=21
leaf #27 score:0.5 ==>lcom3=(0, 0.96476834) ==>targetscore=0.0 ==>targeleaf=26
leaf #29 score:1.0 ==>rfc=(4, 19) ==>targetscore=0.0 ==>targeleaf=28
leaf #32 score:0.5 ==>dit=(3, 7) ==>targetscore=0.0 ==>targeleaf=34
leaf #33 score:1.0 ==>rfc=(4, 19) ==>targetscore=0.5 ==>targeleaf=32
leaf #37 score:0.5 ==>dit=(1, 2) ==>targetscore=0.0 ==>targeleaf=36
leaf #41 score:0.5 ==>loc=(10, 125) ==>targetscore=0.0 ==>targeleaf=40
###Results
# db rx n a b c d acc pd pf prec f g class
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# Traing Testing 579 117 234 49 345 62 60 30 88 71 65 Non-Defective
# Traing Testing 166 345 49 234 117 62 70 40 33 45 65 Defective