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Comprehensive model for software fault prediction

Pradeep Singh
2017 2017 International Conference on Inventive Computing and Informatics (ICICI)  
machine, artificial neural networks, instance-based reasoning, Bayesian-belief networks, decision trees, rule induction, multi-linear regression models, multivariate models, back propagation neural Network  ...  , test effort prediction and quality prediction.  ...  They compare the results of these two neural network models with statistical methods (discriminate analysis and logistic regression) using five quality model parameters [6] .  ... 
doi:10.1109/icici.2017.8365311 fatcat:ljjfetlomrf5dghnneqxoaicaa

Literature Reviews on Applying Artificial Intelligence/Machine Learning to Software Engineering Research Problems: Preliminary

Pornsiri Muenchaisri
2019 Asia-Pacific Software Engineering Conference  
This paper is aimed to explore the application of Artificial Intelligence/Machine Learning (AI/ML) to software engineering research problems.  ...  The author manually reviews papers with some keywords such as machine learning, neural network, and natural language processing.  ...  An approach with neural network, naive Bayes, logistic regression and SVM, DTPre based on decision tree [Moh18] is proposed to predict which pull requests will get reopened in GitHub.  ... 
dblp:conf/apsec/Muenchaisri19 fatcat:6ks33tovbzbafpnq4ffwntinay

Logistic regression and artificial neural network classification models: a methodology review

Stephan Dreiseitl, Lucila Ohno-Machado
2002 Journal of Biomedical Informatics  
Logistic regression and artificial neural networks are the models of choice in many medical data classification tasks.  ...  Finally, we summarize our findings on how quality criteria for logistic regression and artificial neural network models are met in a sample of papers from the medical literature.  ...  Although the functional forms for logistic regression and artificial neural network models are quite different, a network without a hidden layer is actually identical to a logistic regression model if  ... 
doi:10.1016/s1532-0464(03)00034-0 pmid:12968784 fatcat:ij4wflrbzbfj3abbmwmhitceu4

Comparison of Artificial Neural Networks and Logistic Regression Analysis in Pregnancy Prediction Using the In Vitro Fertilization Treatment

Robert Milewski, Anna Justyna Milewska, Teresa Więsak, Allen Morgan
2013 Studies in Logic, Grammar and Rhetoric  
By comparing two statistical models, Multivariable Logistic Regression analysis and Artificial Neural Network it has been demonstrated that Multivariable Logistic Regression analysis is more suitable for  ...  theoretical interest but the Artificial Neural Network method is more useful in clinical prediction.  ...  A lot of hope lies in the application of Artificial Neural Networks (ANNs), which so far gives excellent results in predict- Networks and Logistic Regression...  ... 
doi:10.2478/slgr-2013-0033 fatcat:dcgiy66lc5bfloogtdnuptlrnu

Performance of Aspect-Oriented Software Quality Modelling using Artificial Neural Network Technique

Pankaj Kumar, Sarvottam Dixit, S. K.
2019 International Journal of Computer Applications  
An exact estimation is the key focus of any prediction model. Software quality is one of the basic research issue for software organizations.  ...  Among various soft computing techniques, Artificial Neural Network (ANN) based models are outstanding, which to a great degree needs more research work and tries to find the most sensible model for software  ...  Application of neural networks to software quality 1997 Modeling of a very large telecommunications system Authors introduce the use of the neural networks as a tool for predicting software quality. by  ... 
doi:10.5120/ijca2019918352 fatcat:b3g6ovgztnhx3lrvz6tyumayri

Comparison of artificial neural network and logistic regression models for prediction of mortality in head trauma based on initial clinical data

Behzad Eftekhar, Kazem Mohammad, Hassan Eftekhar Ardebili, Mohammad Ghodsi, Ebrahim Ketabchi
2005 BMC Medical Informatics and Decision Making  
In recent years, outcome prediction models using artificial neural network and multivariable logistic regression analysis have been developed in many areas of health care research.  ...  In this study we have compared the performance of artificial neural network and multivariable logistic regression models, in prediction of outcomes in head trauma and studied the reproducibility of the  ...  Ahmad Reza Eftekhar for his comments and assistance with the editing of this paper. We would also like to thank Mr. Sam Holden Research Assistant at the University of Sydney for his editorial help.  ... 
doi:10.1186/1472-6947-5-3 pmid:15713231 pmcid:PMC551612 fatcat:xnkyreijbncb3ojhpq7rmm5rrm

Indirect Recognition of Predefined Human Activities

Ojan Majidzadeh Gorjani, Antonino Proto, Jan Vanus, Petr Bilik
2020 Sensors  
The work investigates the application of artificial neural networks and logistic regression for the recognition of activities performed by room occupants.  ...  The obtained classifications can benefit the occupant by monitoring the wellbeing of elderly residents and providing optimal air quality and temperature by utilizing heating, ventilation, and air conditioning  ...  Figure 2 shows the application of artificial neural networks using IBM SPSS modeler 18.  ... 
doi:10.3390/s20174829 pmid:32859035 pmcid:PMC7506661 fatcat:wjt46eu2obhadbcig5vgn2ngsi

The possibility of using of artificial neural networks to supporting of inventory management

Irena Nowotyńska
2012 Scientific Journals of Rzeszów University of Technology Series Management and Marketing  
The aim of research was to build and carry out analysis regression and prognostic models of ANN by using Statistica Neural Networks software.  ...  In the paper, the analysis of the possibility of using of artificial neural networks to forecast demand level in trading company was introducted.  ...  REGRESSION MODEL STRUCTURE AND ANALYSIS Demonstration of the applicability of artificial neural networks to predict the demand made on the example of a commercial company -warehouse that sells office supplies  ... 
doi:10.7862/rz.2012.zim.3 fatcat:qdkchji3srbc5dcpmwinjuryia

Analysis on Detecting a Bug in a Software using Machine Learning

2020 International journal of recent technology and engineering  
This can be achieved only through predicting some of the faults in the earlier phase itself such that, it can lead to have a reliable, efficient and a quality software.  ...  In today's scenario, it is very essential in the development phase of a software, predicting a bug and to obtain a successful software.  ...  The model predicts 79% accuracy. K. By the method of Logistic Regression Logistic regression algorithm is a method used for predicting a bug in a software.  ... 
doi:10.35940/ijrte.b4119.079220 fatcat:4j4swpc4vzajtcazv2f5ypyx4q

Design of Decision Support System in the Metastatic Colorectal Cancer Data Set and Its Application

Tuba PALA, Ali Yilmaz CAMURCU
2016 Balkan Journal of Electrical and Computer Engineering  
In the process of data mining, after the phase of data preprocessing, Support Vector Machines, Naive Bayes, Decision Trees, Artificial Neural Networks, Multilayer Perceptron, Logistic Regression algorithms  ...  While the most successful algorithm is Support Vector Machines in Classifying Prediction Model in which only classification algorithms are applied, it is Decision Trees and Artificial Neural Networks which  ...  Veli Berk, academic member in Oncology Department at Erciyes University Medical Faculty, for providing the data of this study, and Assist. Prof. Dr.  ... 
doi:10.17694/bajece.23930 fatcat:wp6auohdhbgb7kakw6hmejzfzq

Statistical and Machine Learning Methods for Software Fault Prediction Using CK Metric Suite: A Comparative Analysis

Yeresime Suresh, Lov Kumar, Santanu Ku. Rath
2014 ISRN Software Engineering  
This paper examines the application of linear regression, logistic regression, and artificial neural network methods for software fault prediction using Chidamber and Kemerer (CK) metrics.  ...  better fault prediction rate when compared with other three neural network models.  ...  Conflict of Interests The authors declare that there is no conflict of interests regarding the publication of this paper.  ... 
doi:10.1155/2014/251083 fatcat:tcxtesmwf5h3nlc3trupgfjbei

Artificial neural network models for forecasting and decision making

Tim Hill, Leorey Marquez, Marcus O'Connor, William Remus
1994 International Journal of Forecasting  
Our intention is to give a balanced assessment of the potential of artificial neural networks for forecasting and decision making models.  ...  Some authors advocate artificial neural networks as a replacement for statistical forecasting and decision models; other authors are concerned that artificial neural networks might be oversold or just  ...  Second, software is readily available for statistical techniques but commercial artificial neural network software, although of good quality, often lags developments in the field.  ... 
doi:10.1016/0169-2070(94)90045-0 fatcat:wdwgh3yu4vcdljonwl3irpwepa

Creating a Comprehensive Method for the Evaluation of a Company

Jakub Horak, Tomas Krulicky, Zuzana Rowland, Veronika Machova
2020 Sustainability  
Artificial neural networks were used to process the data, specifically logistic regressions from the data processed in the Statistica and Mathematica software programmes.  ...  In contrast, the artificial neural structures obtained using the neural network model in the Statistica software were prospective due to their performance, which is almost always above 0.8, and the logical  ...  software programme, neural networks and logistic regression in the Mathematica software programme.  ... 
doi:10.3390/su12219114 fatcat:6374jxkgqveeblauiulp7mssna

Assessing Infant Mortality in Nigeria Using Artificial Neural Network and Logistic Regression Models

M Jaiyeola, S Oyamakin, J Akinyemi, S Adebowale, A Chukwu, O Yusuf
2016 British Journal of Mathematics & Computer Science  
Aim: To examine the suitability of Artificial Neural Network (ANN) in predicting infant mortality and compare its performance with Logistic Regression (LR) model.  ...  Original Research Article Conclusion: The artificial neural network model had a higher sensitivity than the logistic regression model.  ...  Acknowledgement We express our gratitude to the National Population Commission, Abuja, Nigeria and other partners involved in the NDHS.  ... 
doi:10.9734/bjmcs/2016/28870 fatcat:e4uxjxnaenhqtgub2ubjkooehm

Discovering Healthcare Data Patterns by Artificial Intelligence Methods [chapter]

Dalia Kriksciuniene, Virgilijus Sakalauskas, Ivana Ognjanović, Ramo Šendelj
2022 Intelligent Systems Reference Library  
Neural networks.  ...  The chapter provides essential characteristics of methods, traditionally applied in statistics, such as regression analysis, as well as their advanced modifications of logit, probit models, K-means, and  ...  Acknowledgements COST (European Cooperation in Science and Technology) is a funding agency for research and innovation networks.  ... 
doi:10.1007/978-3-030-79353-1_10 fatcat:mpn3wpchyvc5pol5eqei6s3dqm
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