[PDF] Top 20 Software Defect Prediction Using Linear Svm
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Software Defect Prediction Using Linear Svm
... systems, linear SVMs were introduced which were then further also implemented in regression and rank learning ...of linear SVM from which either positive or negative output of the learned function ... See full document
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SQA by Defect prediction: An SVM based In-Appendage Software Development Log Analysis
... Likewise to other multivariate statistical models, the performances of LS-SVM [25]s bases on the combination of several parameters. Attaining of the kernel function is cumbersome and it will depend on each case. ... See full document
7
Early Prediction of Software Defect using Ensemble Learning: A Comparative Study
... classifiers based on a voting technique. Boosting technique is focusing on misclassified training samples that are relearning with several weight values according to the accuracy of classified samples, and then it ... See full document
12
AN HYBRID MULTILAYER PERCEPTRON USING GSO-GA FOR SOFTWARE DEFECT PREDICTION
... locally linear embedding and bolster vector machine (LLE-SVM) is proposed by Shan et ...The SVM is utilized as the essential classifier as a part of the ...in SVM are improved by the technique ... See full document
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A Survey of Software Defect Prediction Using Data Mining Tool
... K.Sankar et.al [11], proposed a system which conquers the issue of deficiency in the processing precision and utilization of the huge number of components. This paper proposed Feature determination method Feature ... See full document
5
Software Defect Prediction Tool based on Neural Network
... real-time Software defects, size and complexity metrics are not sufficient ...[7]. Using Statistical and Machine learning methods, researchers predict the Fault-prone Software ... See full document
7
SQA by Defect prediction: An SVM based In Appendage Software Development Log Analysis
... Fig 7: Line chart comparison of defects logged in process log and defects predicted by ALTA for large size software development The results show that the performance of risk prediction i[r] ... See full document
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A Novel Feature Subset Selection Algorithm for Software Defect Prediction
... Mutual Information theory can also be used for selecting features especially in neural network learning [2]. Here mutual information criterion is used to evaluate a set of candidate features and then an informative ... See full document
5
Prediction of Software Defect Using Linear Twin Core Vector Machine Model
... a defect has to be predicted exactly in order to keep away from the most risk ...program defect prediction module need to be done carefully to keep away from the misclassification of error ...work, ... See full document
6
Software defect prediction using enhanced relevance vector machine
... the SVM produces a sparse model, in some cases the number of support vectors is still quite ...with SVM, RVM can have probabilistic output and more sparse, and kernel function to choose more freely and so ... See full document
5
Effective Estimation of Modules’ Metrics in Software Defect Prediction
... During the past decade, several classification systems have been proposed, which perform predictive modeling efforts for detection of modules that are likely to contain faults. The evaluation of such systems has almost ... See full document
6
STUDIES ON IMPROVING TEXTURE SEGMENTATION PERFORMANCE USING GENERALIZED GAUSSIAN MIXTURE MODEL INTEGRATING DCT AND LBP
... Shahriari-kahkeshi and Askari [14] proposed the plan of a recurrent neural network (RNN) trained Shuffled Frog Leaping Algorithm (SFLA) for the purpose of identifying and following control of non-linear continuous ... See full document
10
Software Vulnerability Prediction Models Based on Complex Network
... vulnerability prediction model based on the complex network of object-oriented software developed in Java ...the software defect information of open source software doesn’t contain the ... See full document
10
Software Defect Association Mining and Defect Correction Effort Prediction
... our defect association prediction and defect correction effort prediction methods are based on the association rule mining method which was first explored by Agrawal et ... See full document
15
Using Artificial Bee Colony Algorithm for MLP Training on Software Defect Prediction
... in software systems continue to be a major problem. Defect prediction is an important topic in software quality research and could help on planning, controlling and executing software ... See full document
9
Comparative Analysis of Software Defect Prediction Techniques
... Software defect prediction is a method of creating machine learning classifiers to predict faulty code snippets, using historical information in computer repositories such as com- plexity of ... See full document
7
Comparative Classifiers for Software Quality Assessment
... The software defect predictive models using the neural network and the RBF techniques are developed in our proposed ...by using subset of data with some ...on software engineering ... See full document
5
Machine learning Methods for Software Defect Prediction a Revisit
... If "Less Mann" projected a unique construction in programmatic Flaw Prophecy with categorization procedures with diverse based Data-sets. These provide a decent recognition of precision with spotting these ... See full document
5
Reproducibility and replicability of software defect prediction studies
... We used Google Scholar to identify citing papers for each of the 208 original studies. On the ‘cited by #papers’ page of each paper we used the ˜Replicate OR ˜Replication OR ˜Replicated string and selected the ‘search ... See full document
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A REVIEW ON SOFTWARE DEFECT PREDICTION USING DATA MINING TECHNIQUES
... string. software.(defect + fault). (software metrics + object oriented metrics + design metrics) Here, ...further using a carefully designed inclusion- exclusion criteria and quality analysis ... See full document
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