2011 IEEE 23rd International Conference on Tools with Artificial Intelligence最新文献_第10页

Impact of Data Sampling on Stability of Feature Selection for Software Measurement Data 数据采样对软件测量数据特征选择稳定性的影响

2011 IEEE 23rd International Conference on Tools with Artificial Intelligence Pub Date : 2011-11-07 DOI: 10.1109/ICTAI.2011.172

Kehan Gao, T. Khoshgoftaar, Amri Napolitano

{"title":"Impact of Data Sampling on Stability of Feature Selection for Software Measurement Data","authors":"Kehan Gao, T. Khoshgoftaar, Amri Napolitano","doi":"10.1109/ICTAI.2011.172","DOIUrl":"https://doi.org/10.1109/ICTAI.2011.172","url":null,"abstract":"Software defect prediction can be considered a binary classification problem. Generally, practitioners utilize historical software data, including metric and fault data collected during the software development process, to build a classification model and then employ this model to predict new program modules as either fault-prone (fp) or not-fault-prone (nfp). Limited project resources can then be allocated according to the prediction results by (for example) assigning more reviews and testing to the modules predicted to be potentially defective. Two challenges often come with the modeling process: (1) high-dimensionality of software measurement data and (2) skewed or imbalanced distributions between the two types of modules (fp and nfp) in those datasets. To overcome these problems, extensive studies have been dedicated towards improving the quality of training data. The commonly used techniques are feature selection and data sampling. Usually, researchers focus on evaluating classification performance after the training data is modified. The present study assesses a feature selection technique from a different perspective. We are more interested in studying the stability of a feature selection method, especially in understanding the impact of data sampling techniques on the stability of feature selection when using the sampled data. Some interesting findings are found based on two case studies performed on datasets from two real-world software projects.","PeriodicalId":332661,"journal":{"name":"2011 IEEE 23rd International Conference on Tools with Artificial Intelligence","volume":"147 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132373625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 18

A Hybrid Consensus and Clustering Method for Protein Structure Selection 蛋白质结构选择的混合共识和聚类方法

2011 IEEE 23rd International Conference on Tools with Artificial Intelligence Pub Date : 2011-11-07 DOI: 10.1109/ICTAI.2011.10

Qingguo Wang, Yingzi Shang, Dong Xu

引用次数: 0

Developing Strategies for Improving Planning and Scheduling of Actions in RTS Games 改进RTS游戏中行动计划和调度的发展策略

2011 IEEE 23rd International Conference on Tools with Artificial Intelligence Pub Date : 2011-11-07 DOI: 10.1109/ICTAI.2011.21

A. A. Branquinho, C. R. Lopes, Thiago F. Naves

引用次数: 1

Incremental Kernel Mapping Algorithms for Scalable Recommender Systems 可扩展推荐系统的增量核映射算法

2011 IEEE 23rd International Conference on Tools with Artificial Intelligence Pub Date : 2011-11-07 DOI: 10.1109/ICTAI.2011.183

M. Ghazanfar, S. Szedmák, A. Prügel-Bennett

引用次数: 10

Artifacting and Regulating the Environment of a Virtual Organization 虚拟组织环境的营造与调节

2011 IEEE 23rd International Conference on Tools with Artificial Intelligence Pub Date : 2011-11-07 DOI: 10.1109/ICTAI.2011.88

Sergio Esparcia, Roberto Centeno, Ramón Hermoso, E. Argente

引用次数: 7

Self-Organized Hierarchical Methods for Time Series Forecasting 时间序列预测的自组织分层方法

2011 IEEE 23rd International Conference on Tools with Artificial Intelligence Pub Date : 2011-11-07 DOI: 10.1109/ICTAI.2011.180

Fuad Mousse Abinader Jr., A. C. S. D. Queiroz, Daniel W. Honda

引用次数: 5

Optimal One-Max Strategy with Dynamic Island Models

2011 IEEE 23rd International Conference on Tools with Artificial Intelligence Pub Date : 2011-11-07 DOI: 10.1109/ICTAI.2011.79

Adrien Goëffon, F. Lardeux

引用次数: 3

Adding Constraints and Flexible Preferences in Travel Reservation Systems 在旅行预订系统中增加约束和灵活的偏好

2011 IEEE 23rd International Conference on Tools with Artificial Intelligence Pub Date : 2011-11-07 DOI: 10.1109/ICTAI.2011.181

S. Benferhat, Abdelhamid Boudjelida

引用次数: 2

Multi-view Transfer Learning with Adaboost Adaboost的多视图迁移学习

2011 IEEE 23rd International Conference on Tools with Artificial Intelligence Pub Date : 2011-11-07 DOI: 10.1109/ICTAI.2011.65

Zhijie Xu, Shiliang Sun

引用次数: 29

A Combinatorial Optimisation Approach to the Design of Dual Parented Long-Reach Passive Optical Networks 双父级长程无源光网络的组合优化设计

2011 IEEE 23rd International Conference on Tools with Artificial Intelligence Pub Date : 2011-11-07 DOI: 10.1109/ICTAI.2011.123

Hadrien Cambazard, D. Mehta, B. O’Sullivan, L. Quesada, M. Ruffini, D. Payne, L. Doyle

{"title":"A Combinatorial Optimisation Approach to the Design of Dual Parented Long-Reach Passive Optical Networks","authors":"Hadrien Cambazard, D. Mehta, B. O’Sullivan, L. Quesada, M. Ruffini, D. Payne, L. Doyle","doi":"10.1109/ICTAI.2011.123","DOIUrl":"https://doi.org/10.1109/ICTAI.2011.123","url":null,"abstract":"We present an application focused on the design of resilient long-reach passive optical networks. We specifically consider dual parented networks whereby each customer must be connected to two metro sites via a local exchange sites. An important property of such a placement is resilience to single metro node failure. The objective of the application is to determine the optimal position of a set of metro-nodes such that the total optical fibre length is minimised. We prove that the decision variant of this problem is NP-Complete. We present three alternative combinatorial optimisation approaches to finding an optimal metro node placement using: a mixed integer linear programming formulation of the problem, a hybrid approach that uses clustering as a preprocessing step, and, finally, a local search approach. We consider a detailed case-study based on a network for Ireland. The hybrid approach scales well and finds solutions that are close to optimal, with a runtime that is two orders-of-magnitude better than the MIP model. The local search approach is consistently good on all benchmarks.","PeriodicalId":332661,"journal":{"name":"2011 IEEE 23rd International Conference on Tools with Artificial Intelligence","volume":"143 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124578993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6