计算机科学论坛--weka functional tree算法的输出结果不明白！！

functional tree和logistic model tree的inner nodes不是一个回归公式吗，为什么weka的输出结果是两个互为负的回归公式。而且最后的leaves node后class1和class2是什么标准分？
下面一个结果的示例，两种模型的weka输出结果类似，所以只放上functional tree的输出结果。
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=== Run information ===

Scheme:weka.classifiers.trees.FT -I 15 -F 0 -M 15 -W 0.0
Relation: training-weka.filters.unsupervised.attribute.Remove-R1-weka.filters.unsupervised.attribute.Remove-R3-10,34-1171,1228-1302-weka.filters.unsupervised.attribute.Remove-R22,36-38,40,45,49-50,59,62,66-77,79
Instances:204
Attributes:59
              MW
              AMW
              nAT
              nSK
              nBT
              nBO
              nBM
              SCBO
              nCIC
              nCIR
              RBN
              RBF
              nDB
              nTB
              nAB
              nH
              nC
              nN
              nO
              nP
              nS
              nCL
              nBR
              nX
              nCp
              nCs
              nCt
              nCq
              nCrH2
              nCrHR
              nCrR2
              nCaH
              nCaR
              nCconjR
              nNCO
              nCOOHPh
              nCOOR
              nCOORPh
              nCONHR
              nCONR2
              nOCON
              nCOXPh
              nCO
              nCONN
              nNH2
              nNH2Ph
              nNHR
              nNHRPh
              nNR2
              nNR2Ph
              nCN
              nNO2Ph
              nOH
              nOHPh
              nOHp
              nPhX
              nHDon
              nHAcc
              judgement
Test mode:10-fold cross-validation

=== Classifier model (full training set) ===

FT tree
------------------

N0#1 <= 0.538508
| N0#2 <= 0.188679: FT_1:15/45 (76)
| N0#2 > 0.188679: FT_2:15/45 (32)
N0#1 > 0.538508: FT_3:15/30 (96)

Number of Leaves : 3

Size of the Tree : 5
FT_N0#1:
Class 0 :
-1.45 +
[MW] * 0    +
[nCIR] * 0.1  +
[nDB] * -0.14 +
[nN] * 0.5  +
[nS] * 0.36 +
[nCp] * 0.17 +
[nCrH2] * 0.07 +
[nCrHR] * 0.21 +
[nCrR2] * 0.43 +
[nCaR] * 0.07 +
[nCOORPh] * -0.58 +
[nNH2Ph] * 0.47 +
[nNR2] * -0.28 +
[nPhX] * 0.28

Class 1 :
1.45 +
[MW] * 0 +
[nCIR] * -0.1 +
[nDB] * 0.14 +
[nN] * -0.5 +
[nS] * -0.36 +
[nCp] * -0.17 +
[nCrH2] * -0.07 +
[nCrHR] * -0.21 +
[nCrR2] * -0.43 +
[nCaR] * -0.07 +
[nCOORPh] * 0.58 +
[nNH2Ph] * -0.47 +
[nNR2] * 0.28 +
[nPhX] * -0.28

FT_N0#2:
Class 0 :
-2.22 +
[MW] * 0.01 +
[nCIR] * 0.1  +
[nDB] * -0.14 +
[nN] * 0.5  +
[nS] * 0.36 +
[nBR] * 1.52 +
[nCp] * 0.17 +
[nCq] * 1.56 +
[nCrH2] * 0.18 +
[nCrHR] * 0.56 +
[nCrR2] * 1.95 +
[nCaR] * 0.07 +
[nCOOR] * -0.93 +
[nCOORPh] * -0.58 +
[nCONHR] * -0.54 +
[nCONR2] * 1.52 +
[nCOXPh] * -0.74 +
[nNH2] * -0.77 +
[nNH2Ph] * 0.47 +
[nNR2] * -0.28 +
[nNR2Ph] * 1.31 +
[nPhX] * 0.8  +
[nHAcc] * -0.13

Class 1 :
2.22 +
[MW] * -0.01 +
[nCIR] * -0.1 +
[nDB] * 0.14 +
[nN] * -0.5 +
[nS] * -0.36 +
[nBR] * -1.52 +
[nCp] * -0.17 +
[nCq] * -1.56 +
[nCrH2] * -0.18 +
[nCrHR] * -0.56 +
[nCrR2] * -1.95 +
[nCaR] * -0.07 +
[nCOOR] * 0.93 +
[nCOORPh] * 0.58 +
[nCONHR] * 0.54 +
[nCONR2] * -1.52 +
[nCOXPh] * 0.74 +
[nNH2] * 0.77 +
[nNH2Ph] * -0.47 +
[nNR2] * 0.28 +
[nNR2Ph] * -1.31 +
[nPhX] * -0.8 +
[nHAcc] * 0.13

FT_1:
Class 0 :
-1.92 +
[MW] * 0.01 +
[nBT] * -0.06 +
[nCIR] * 0.1  +
[RBF] * 4.33 +
[nDB] * -0.45 +
[nH] * -0.27 +
[nN] * 0.5  +
[nS] * 2.88 +
[nBR] * 1.52 +
[nCp] * 1.08 +
[nCq] * 1.56 +
[nCrH2] * 0.18 +
[nCrHR] * 0.56 +
[nCrR2] * 1.95 +
[nCaR] * 0.07 +
[nCOOHPh] * 1.16 +
[nCOOR] * -0.93 +
[nCOORPh] * -0.58 +
[nCONHR] * -0.54 +
[nCONR2] * 1.52 +
[nCOXPh] * -0.74 +
[nNH2] * -0.77 +
[nNH2Ph] * 0.47 +
[nNR2] * -0.28 +
[nNR2Ph] * 1.31 +
[nNO2Ph] * 1.8  +
[nPhX] * 0.8  +
[nHDon] * -1.19 +
[nHAcc] * -0.13

Class 1 :
1.92 +
[MW] * -0.01 +
[nBT] * 0.06 +
[nCIR] * -0.1 +
[RBF] * -4.33 +
[nDB] * 0.45 +
[nH] * 0.27 +
[nN] * -0.5 +
[nS] * -2.88 +
[nBR] * -1.52 +
[nCp] * -1.08 +
[nCq] * -1.56 +
[nCrH2] * -0.18 +
[nCrHR] * -0.56 +
[nCrR2] * -1.95 +
[nCaR] * -0.07 +
[nCOOHPh] * -1.16 +
[nCOOR] * 0.93 +
[nCOORPh] * 0.58 +
[nCONHR] * 0.54 +
[nCONR2] * -1.52 +
[nCOXPh] * 0.74 +
[nNH2] * 0.77 +
[nNH2Ph] * -0.47 +
[nNR2] * 0.28 +
[nNR2Ph] * -1.31 +
[nNO2Ph] * -1.8 +
[nPhX] * -0.8 +
[nHDon] * 1.19 +
[nHAcc] * 0.13

FT_2:
Class 0 :
-0.83 +
[MW] * 0.01 +
[nBT] * -0.03 +
[nCIR] * -0.03 +
[nDB] * -0.14 +
[nN] * -0.65 +
[nS] * 0.36 +
[nBR] * 1.52 +
[nCp] * 0.17 +
[nCq] * 2.29 +
[nCrH2] * 0.18 +
[nCrHR] * 0.56 +
[nCrR2] * 1.95 +
[nCaH] * 0.05 +
[nCaR] * 0.07 +
[nCconjR] * 0.7  +
[nCOOHPh] * -0.64 +
[nCOOR] * -2.8 +
[nCOORPh] * -0.58 +
[nCONHR] * -0.54 +
[nCONR2] * 1.52 +
[nCOXPh] * -2.31 +
[nCO] * 0.36 +
[nNH2] * -0.77 +
[nNH2Ph] * 0.47 +
[nNHR] * 1.57 +
[nNR2] * -0.28 +
[nNR2Ph] * 2    +
[nOH] * -1.16 +
[nPhX] * 0.8  +
[nHAcc] * -0.13

Class 1 :
0.83 +
[MW] * -0.01 +
[nBT] * 0.03 +
[nCIR] * 0.03 +
[nDB] * 0.14 +
[nN] * 0.65 +
[nS] * -0.36 +
[nBR] * -1.52 +
[nCp] * -0.17 +
[nCq] * -2.29 +
[nCrH2] * -0.18 +
[nCrHR] * -0.56 +
[nCrR2] * -1.95 +
[nCaH] * -0.05 +
[nCaR] * -0.07 +
[nCconjR] * -0.7 +
[nCOOHPh] * 0.64 +
[nCOOR] * 2.8 +
[nCOORPh] * 0.58 +
[nCONHR] * 0.54 +
[nCONR2] * -1.52 +
[nCOXPh] * 2.31 +
[nCO] * -0.36 +
[nNH2] * 0.77 +
[nNH2Ph] * -0.47 +
[nNHR] * -1.57 +
[nNR2] * 0.28 +
[nNR2Ph] * -2 +
[nOH] * 1.16 +
[nPhX] * -0.8 +
[nHAcc] * 0.13

FT_3:
Class 0 :
0.02 +
[MW] * 0    +
[nBT] * -0.02 +
[nCIR] * 0.1  +
[RBF] * -1.76 +
[nDB] * 0.05 +
[nN] * 0.5  +
[nP] * -0.89 +
[nS] * 1.28 +
[nCL] * -0.16 +
[nCp] * 0.17 +
[nCs] * 0.03 +
[nCrH2] * 0.07 +
[nCrHR] * 0.21 +
[nCrR2] * 0.43 +
[nCaR] * 0.07 +
[nCOORPh] * -0.58 +
[nOCON] * -0.89 +
[nNH2Ph] * 0.06 +
[nNR2] * -0.78 +
[nNO2Ph] * 0.34 +
[nOHPh] * -0.31 +
[nPhX] * 0.28

Class 1 :
-0.02 +
[MW] * 0 +
[nBT] * 0.02 +
[nCIR] * -0.1 +
[RBF] * 1.76 +
[nDB] * -0.05 +
[nN] * -0.5 +
[nP] * 0.89 +
[nS] * -1.28 +
[nCL] * 0.16 +
[nCp] * -0.17 +
[nCs] * -0.03 +
[nCrH2] * -0.07 +
[nCrHR] * -0.21 +
[nCrR2] * -0.43 +
[nCaR] * -0.07 +
[nCOORPh] * 0.58 +
[nOCON] * 0.89 +
[nNH2Ph] * -0.06 +
[nNR2] * 0.78 +
[nNO2Ph] * -0.34 +
[nOHPh] * 0.31 +
[nPhX] * -0.28

Time taken to build model: 0.44seconds

=== Stratified cross-validation ===
=== Summary ===

Correctly Classified Instances         157               76.9608 %
Incorrectly Classified Instances        47               23.0392 %
Kappa statistic                          0.5389
Mean absolute error                      0.2359
Root mean squared error                  0.4548
Relative absolute error                 47.3282 %
Root relative squared error             91.1099 %
Total Number of Instances              204

=== Detailed Accuracy By Class ===

               TP Rate   FP Rate   Precision   Recall  F-Measure   ROC Area  Class
                 0.759     0.219      0.796     0.759     0.777      0.771    N
                 0.781     0.241      0.743     0.781     0.761      0.771    R
Weighted Avg.    0.77      0.229      0.771     0.77      0.77       0.771

=== Confusion Matrix ===

  a  b   <-- classified as
82 26 |  a = N
21 75 |  b = R


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