-
2
-
-
49349089233
-
Benchmarking classification models for software defect prediction: A proposed framework and novel findings
-
S. Lessmann, B. Baesens, C. Mues and S. Pietsch, Benchmarking classification models for software defect prediction: A proposed framework and novel findings, IEEE Transactions on Software Engineering 34(4) 2008, 485-496.
-
(2008)
IEEE Transactions on Software Engineering
, vol.34
, Issue.4
, pp. 485-496
-
-
Lessmann, S.1
Baesens, B.2
Mues, C.3
Pietsch, S.4
-
5
-
-
0031192278
-
Application of neural networks to software quality modeling of a very large telecommunications system
-
T. M. Khoshgoftaar, E. B. Allen, J. P. Hudepohl and S. J. Aud, Application of neural networks to software quality modeling of a very large telecommunications system, IEEE Transactions on Neural Networks 8(4) 1997, 902-909.
-
(1997)
IEEE Transactions on Neural Networks
, vol.8
, Issue.4
, pp. 902-909
-
-
Khoshgoftaar, T.M.1
Allen, E.B.2
Hudepohl, J.P.3
Aud, S.J.4
-
6
-
-
0034155864
-
Classification-tree models of software-quality over multiple releases
-
T. M. Khoshgoftaar, E. B. Allen, W. D. Jones and J. P. Hudepohl, Classification-tree models of software-quality over multiple releases, IEEE Transactions on Reliability 49(1) 2000, 4-11.
-
(2000)
IEEE Transactions on Reliability
, vol.49
, Issue.1
, pp. 4-11
-
-
Khoshgoftaar, T.M.1
Allen, E.B.2
Jones, W.D.3
Hudepohl, J.P.4
-
7
-
-
0036891333
-
Using regression trees to classify faultprone software modules
-
T. M. Khoshgoftaar, E. B. Allen and J. Deng, Using regression trees to classify faultprone software modules, IEEE Transactions on Reliability 51(4) 2002, 455-462.
-
(2002)
IEEE Transactions on Reliability
, vol.51
, Issue.4
, pp. 455-462
-
-
Khoshgoftaar, T.M.1
Allen, E.B.2
Deng, J.3
-
8
-
-
0141924286
-
Analogy-based practical classification rules for software quality estimation
-
T. M. Khoshgoftaar and N. Seliya, Analogy-based practical classification rules for software quality estimation, Empirical Software Engineering 8(4) (2003) 325-350.
-
(2003)
Empirical Software Engineering
, vol.8
, Issue.4
, pp. 325-350
-
-
Khoshgoftaar, T.M.1
Seliya, N.2
-
10
-
-
0006473387
-
Evaluating techniques for generating metric-based classification trees
-
A. A. Porter and R. W. Selby, Evaluating techniques for generating metric-based classification trees, Journal of Systems and Software 12(3) (1990) 209-218.
-
(1990)
Journal of Systems and Software
, vol.12
, Issue.3
, pp. 209-218
-
-
Porter, A.A.1
Selby, R.W.2
-
11
-
-
0035152294
-
Comparing case-based reasoning classifiers for predicting high risk software components
-
K. El-Emam, S. Benlarbi, N. Goel and S. N. Rai, Comparing case-based reasoning classifiers for predicting high risk software components, Journal of Systems and Software 55(3) (2001) 301-310.
-
(2001)
Journal of Systems and Software
, vol.55
, Issue.3
, pp. 301-310
-
-
El-Emam, K.1
Benlarbi, S.2
Goel, N.3
Rai, S.N.4
-
13
-
-
40749135790
-
Predicting defect-prone software modules using support vector machines
-
K. O. Elish and M. O. Elish, Predicting defect-prone software modules using support vector machines, Journal of Systems and Software 81(5) (2008) 649-660.
-
(2008)
Journal of Systems and Software
, vol.81
, Issue.5
, pp. 649-660
-
-
Elish, K.O.1
Elish, M.O.2
-
14
-
-
77149120435
-
Empirical evaluation of classifiers for software risk management
-
Y. Peng, G. Kou, G. Wang, H. Wang and F. Ko, Empirical evaluation of classifiers for software risk management, International Journal of Information Technology and Decision Making 8(4) (2009) 749-768.
-
(2009)
International Journal of Information Technology and Decision Making
, vol.8
, Issue.4
, pp. 749-768
-
-
Peng, Y.1
Kou, G.2
Wang, G.3
Wang, H.4
Ko, F.5
-
15
-
-
84857575716
-
User p based software defect detection algorithms selection using MCDM
-
doi:10.1016/j.ins.2010.04.019
-
Y. Peng, G. Wang and H. Wang, User p based software defect detection algorithms selection using MCDM, Information Sciences (2010), doi: 10.1016/j.ins.2010.04.019.
-
(2010)
Information Sciences
-
-
Peng, Y.1
Wang, G.2
Wang, H.3
-
18
-
-
0033161922
-
A controlled experiment to assess the benefits of estimating with analogy and regression models
-
I. Myrtveit and E. Stensrud, A controlled experiment to assess the benefits of estimating with analogy and regression models, IEEE Transactions on Software Engineering 25(4) 1999,510-525.
-
(1999)
IEEE Transactions on Software Engineering
, vol.25
, Issue.4
, pp. 510-525
-
-
Myrtveit, I.1
Stensrud, E.2
-
19
-
-
22944440671
-
Reliability and validity in comparative studies of software prediction models
-
I. Myrtveit, E. Stensrud and M. Shepperd, Reliability and validity in comparative studies of software prediction models, IEEE Transactions on Software Engineering 31(5) 2005,380-391.
-
(2005)
IEEE Transactions on Software Engineering
, vol.31
, Issue.5
, pp. 380-391
-
-
Myrtveit, I.1
Stensrud, E.2
Shepperd, M.3
-
20
-
-
0035506767
-
Comparing software prediction techniques using simulation
-
DOI 10.1109/32.965341
-
M. Shepperd and G. Kadoda, Comparing software prediction techniques using simulation, IEEE Transactions on Software Engineering 27(11) 2001, 1014-1022. (Pubitemid 33106029)
-
(2001)
IEEE Transactions on Software Engineering
, vol.27
, Issue.11
, pp. 1014-1022
-
-
Shepperd, M.1
Kadoda, G.2
-
21
-
-
0003443508
-
-
McGraw-Hill, Columbus, OH
-
T. L. Saaty, The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation (McGraw-Hill, Columbus, OH, 1980).
-
(1980)
The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation
-
-
Saaty, T.L.1
-
23
-
-
0034250160
-
An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, boosting, and randomization
-
T. G. Dietterich, An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, boosting, and randomization, Machine Learning 40(2) (2000) 139-157.
-
(2000)
Machine Learning
, vol.40
, Issue.2
, pp. 139-157
-
-
Dietterich, T.G.1
-
25
-
-
0031361611
-
Machine learning research: Four current directions
-
T. G. Dietterich, Machine learning research: Four current directions, AI Magazine 18 (1997) 97-136.
-
(1997)
AI Magazine
, vol.18
, pp. 97-136
-
-
Dietterich, T.G.1
-
26
-
-
0142103425
-
A study of adaboost with naïive Bayesian classifiers: Weakness and improvement
-
K. M. Ting and Z. Zheng, A study of AdaBoost with Naïive Bayesian classifiers: Weakness and improvement, Computational Intelligence 19(2) (2003) 186-200.
-
(2003)
Computational Intelligence
, vol.19
, Issue.2
, pp. 186-200
-
-
Ting, K.M.1
Zheng, Z.2
-
27
-
-
33646867863
-
Recognizing strong and weak opinion clauses
-
T. Wilson, J. Wiebe and R. Hwa, Recognizing strong and weak opinion clauses, Computational Intelligence 22(2) (2006) 73-99.
-
(2006)
Computational Intelligence
, vol.22
, Issue.2
, pp. 73-99
-
-
Wilson, T.1
Wiebe, J.2
Hwa, R.3
-
30
-
-
80053403826
-
Ensemble methods in machine learning
-
J. Kittler and F. Roli eds., New York, Springer-Verlag
-
T. G. Dietterich, Ensemble methods in machine learning, in J. Kittler and F. Roli (eds.) First International Workshop on Multiple Classifier Systems, Lecture Notes in Computer Science, Vol. 1857 (New York, Springer-Verlag, 2000b), pp. 1-15.
-
(2000)
First International Workshop on Multiple Classifier Systems, Lecture Notes in Computer Science
, vol.1857
, pp. 1-15
-
-
Dietterich, T.G.1
-
31
-
-
0032645080
-
An empirical comparison of voting classification algorithms: Bagging, boosting, and variants
-
E. Bauer and R. Kohavi, An empirical comparison of voting classification algorithms: Bagging, boosting, and variants, Machine Learning 36(1/2) (1999) 105-139.
-
(1999)
Machine Learning
, vol.36
, Issue.1-2
, pp. 105-139
-
-
Bauer, E.1
Kohavi, R.2
-
32
-
-
0030211964
-
Bagging predictors
-
L. Breiman, Bagging predictors, Machine Learning 24(2) (1996) 123-140.
-
(1996)
Machine Learning
, vol.24
, Issue.2
, pp. 123-140
-
-
Breiman, L.1
-
33
-
-
0030344230
-
Heuristics of instability in model selection
-
L. Breiman, Heuristics of instability in model selection, The Annals of Statistics 24(6) (1994) 2350-2383.
-
(1994)
The Annals of Statistics
, vol.24
, Issue.6
, pp. 2350-2383
-
-
Breiman, L.1
-
35
-
-
0025448521
-
The strength of weak learnability
-
R. Schapire, The strength of weak learnability, Machine Learning 5(2) (1990) 197-227.
-
(1990)
Machine Learning
, vol.5
, Issue.2
, pp. 197-227
-
-
Schapire, R.1
-
36
-
-
0031211090
-
A decision-theoretic generalization of on-line learning and an application to boosting
-
Y. Freund and R. E. Schapire, A decision-theoretic generalization of on-line learning and an application to boosting, Journal of Computer and System Sciences 55 (1997) 119-139.
-
(1997)
Journal of Computer and System Sciences
, vol.55
, pp. 119-139
-
-
Freund, Y.1
Schapire, R.E.2
-
37
-
-
0026692226
-
Stacked generalization
-
D. H. Wolpert, Stacked generalization, Neural Networks 5 (1992) 241-259.
-
(1992)
Neural Networks
, vol.5
, pp. 241-259
-
-
Wolpert, D.H.1
-
38
-
-
58149235001
-
A descriptive framework for the field of data mining and knowledge discovery
-
Y. Peng, G. Kou, Y. Shi and Z. Chen, A descriptive framework for the field of data mining and knowledge discovery, International Journal of Information Technology and Decision Making 7(4) (2008) 639-682.
-
(2008)
International Journal of Information Technology and Decision Making
, vol.7
, Issue.4
, pp. 639-682
-
-
Peng, Y.1
Kou, G.2
Shi, Y.3
Chen, Z.4
-
40
-
-
85054435084
-
Neural network ensembles, cross validation, and active learning
-
Tesauro, G., Touretzky, D. and Leen, T. eds., Cambridge, MA, MIT Press
-
A. Krogh and J. Vedelsby, Neural network ensembles, cross validation, and active learning, in Tesauro, G., Touretzky, D. and Leen, T. (eds.), Advances in Neural Information Processing Systems, Vol. 7 (Cambridge, MA, MIT Press, 1995), pp. 231-238.
-
(1995)
Advances in Neural Information Processing Systems
, vol.7
, pp. 231-238
-
-
Krogh, A.1
Vedelsby, J.2
-
41
-
-
0003802343
-
-
Wadsworth International Group, Belmont, California
-
L. Breiman, J. H. Friedman, R. A. Olshen and C. J. Stone, Classification and Regression Trees (Wadsworth International Group, Belmont, California, 1984).
-
(1984)
Classification and Regression Trees
-
-
Breiman, L.1
Friedman, J.H.2
Olshen, R.A.3
Stone, C.J.4
-
42
-
-
85156137079
-
Scaling up the accuracy of Naïive Bayes classifiers: A decision tree hybrid
-
E. Simoudis, J. W. Han and U. Fayyad eds. , Portland, OR. Menlo Park, CA, AAAI Press
-
R. Kohavi, Scaling up the accuracy of Naïive Bayes classifiers: A decision tree hybrid, in E. Simoudis, J. W. Han and U. Fayyad (eds.), Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (Portland, OR. Menlo Park, CA, AAAI Press, 1996), pp. 202-207.
-
(1996)
Proceedings of the Second International Conference on Knowledge Discovery and Data Mining
, pp. 202-207
-
-
Kohavi, R.1
-
44
-
-
0000521473
-
Ridge estimators in logistic regression
-
S. Le Cessie and J. C. Houwelingen, Ridge estimators in logistic regression, Applied Statistics 41(1) (1992) 191-201.
-
(1992)
Applied Statistics
, vol.41
, Issue.1
, pp. 191-201
-
-
Le Cessie, S.1
Houwelingen, J.C.2
-
46
-
-
0003120218
-
Fast training of support vector machines using sequential minimal optimization
-
B. Schotolkopf, C. J. C. Burges and A. Smola eds., MIT Press
-
J. C. Platt, Fast training of support vector machines using sequential minimal optimization, in B. Schotolkopf, C. J. C. Burges and A. Smola (eds.), Advances in Kernel Methods-Support Vector Learning (MIT Press, 1998), pp. 185-208.
-
(1998)
Advances in Kernel Methods-Support Vector Learning
, pp. 185-208
-
-
Platt, J.C.1
-
48
-
-
0031269184
-
On the optimality of the simple Bayesian classifier under zero-one loss
-
P. Domingos and M. Pazzani, On the optimality of the simple Bayesian classifier under zero-one loss, Machine Learning 29(203) (1997) 103-130.
-
(1997)
Machine Learning
, vol.29
, Issue.203
, pp. 103-130
-
-
Domingos, P.1
Pazzani, M.2
-
51
-
-
84948977233
-
The power of decision tables
-
N. Lavrac and S. Wrobel eds., Springer-Verlag, Iraklion, Crete, Greece
-
R. Kohavi, The power of decision tables, in N. Lavrac and S. Wrobel (eds.), Proceedings of the Eighth European Conference on Machine Learning (Springer-Verlag, Iraklion, Crete, Greece, 1995), pp. 174-189.
-
(1995)
Proceedings of the Eighth European Conference on Machine Learning
, pp. 174-189
-
-
Kohavi, R.1
-
53
-
-
0025700933
-
How to make a decision: The analytic hierarchy process
-
T. L. Saaty, How to make a decision: The analytic hierarchy process, European Journal of Operational Research 48 (1990) 9-26.
-
(1990)
European Journal of Operational Research
, vol.48
, pp. 9-26
-
-
Saaty, T.L.1
-
55
-
-
53449102906
-
Decision making with the analytic hierarchy process
-
T. L. Saaty, Decision making with the analytic hierarchy process, International Journal of Services Sciences 1(1) (2008) 83-98.
-
(2008)
International Journal of Services Sciences
, vol.1
, Issue.1
, pp. 83-98
-
-
Saaty, T.L.1
-
56
-
-
49449122896
-
A scaling method for priorities in hierarchical structures
-
T. L. Saaty, A scaling method for priorities in hierarchical structures, Journal of Mathematical Psychology 15(3) (1977) 234-281.
-
(1977)
Journal of Mathematical Psychology
, vol.15
, Issue.3
, pp. 234-281
-
-
Saaty, T.L.1
-
57
-
-
0002425683
-
The analytic hierarchy process-a survey of the method and its applications
-
F. Zahedi, The analytic hierarchy process-a survey of the method and its applications, Interfaces 16(4) (1986) 96-108.
-
(1986)
Interfaces
, vol.16
, Issue.4
, pp. 96-108
-
-
Zahedi, F.1
-
58
-
-
35348994805
-
Integrated analytic hierarchy process and its applications - A literature review
-
W. Ho, Integrated analytic hierarchy process and its applications - A literature review, European Journal of Operational Research 186(1) 211-228.
-
European Journal of Operational Research
, vol.186
, Issue.1
, pp. 211-228
-
-
Ho, W.1
-
59
-
-
0035414668
-
Interval evaluations in the analytic hierarchy process by possibility analysis
-
K. Sugihara and H. Tanaka, Interval evaluations in the analytic hierarchy process by possibility analysis, Computational Intelligence 17(3) (2001) 567-579.
-
(2001)
Computational Intelligence
, vol.17
, Issue.3
, pp. 567-579
-
-
Sugihara, K.1
Tanaka, H.2
-
60
-
-
45749089732
-
Ranking decision alternatives by integrated DEA, AHP and gower plot techniques
-
H. Li and L. Ma, Ranking decision alternatives by integrated DEA, AHP and gower plot techniques, International Journal of Information Technology & Decision Making 7(2) (2008) 241-258.
-
(2008)
International Journal of Information Technology & Decision Making
, vol.7
, Issue.2
, pp. 241-258
-
-
Li, H.1
Ma, L.2
-
63
-
-
0034224993
-
An investigation of machine learning based prediction systems
-
C. Mair, G. Kadoda, M. Leflel, L. Phapl, K. Schofield, M. Shepperd and S. Webster, An investigation of machine learning based prediction systems, Journal of Systems Software 53(1) (2000) 23-29.
-
(2000)
Journal of Systems Software
, vol.53
, Issue.1
, pp. 23-29
-
-
Mair, C.1
Kadoda, G.2
Leflel, M.3
Phapl, L.4
Schofield, K.5
Shepperd, M.6
Webster, S.7
-
64
-
-
44349135014
-
Empirical assessment of machine learning based software defect prediction techniques
-
V. U. B. Challagulla, F. B. Bastani, I. Y. Raymond and A. Paul, Empirical assessment of machine learning based software defect prediction techniques, International Journal on Artificial Intelligence Tools 17(2) (2008) 389-400.
-
(2008)
International Journal on Artificial Intelligence Tools
, vol.17
, Issue.2
, pp. 389-400
-
-
Challagulla, V.U.B.1
Bastani, F.B.2
Raymond, I.Y.3
Paul, A.4
|