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Comprehensive model for software fault prediction
2017
2017 International Conference on Inventive Computing and Informatics (ICICI)
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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
2019
Asia-Pacific Software Engineering Conference
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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
2002
Journal of Biomedical Informatics
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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
2013
Studies in Logic, Grammar and Rhetoric
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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
2019
International Journal of Computer Applications
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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
2005
BMC Medical Informatics and Decision Making
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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
2020
Sensors
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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
2012
Scientific Journals of Rzeszów University of Technology Series Management and Marketing
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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
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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
2016
Balkan Journal of Electrical and Computer Engineering
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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
2014
ISRN Software Engineering
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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
1994
International Journal of Forecasting
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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
2020
Sustainability
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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
2016
British Journal of Mathematics & Computer Science
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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]
2022
Intelligent Systems Reference Library
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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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