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Generic Methods for Multi-criteria Evaluation [chapter]

Niklas Lavesson, Paul Davidsson
2008 Proceedings of the 2008 SIAM International Conference on Data Mining  
Acknowledgments The authors would like to thank Johan Holmgren at Blekinge Institute of Technology for fruitful discussions about the candidate evaluation function (CEF).  ...  In this study, we use the term multi-criteria (MC) evaluation for multi-metric evaluation.  ...  Next we will explain the concept of multi-criteria evaluation. In Section 2 we then present three existing generic multi-criteria methods.  ... 
doi:10.1137/1.9781611972788.49 dblp:conf/sdm/LavessonD08 fatcat:qm52zq472rhkhhhawj2n7wygr4

A Study on Software Metrics based Software Defect Prediction using Data Mining and Machine Learning Techniques

Manjula.C.M. Prasad, Lilly Florence Florence, Arti Arya3
2015 International Journal of Database Theory and Application  
The main objective of paper is to help developers identify defects based on existing software metrics using data mining techniques and thereby improve the software quality.In this paper, variousclassification  ...  techniquesare revisitedwhich are employed for software defect prediction using software metrics in the literature.  ...  The various data mining classifier algorithms namely J48, Random Forest, and Naive Bayesian Classifier (NBC) are evaluated based on various criteria like ROC, Precision, MAE, RAE etc.  ... 
doi:10.14257/ijdta.2015.8.3.15 fatcat:pk5okarex5g55df2e5uxorhp54

AMORI: A Metric-based One Rule Inducer [chapter]

Niklas Lavesson, Paul Davidsson
2009 Proceedings of the 2009 SIAM International Conference on Data Mining  
Acknowledgments We would like to thank Fahad Khalid for his ideas about metric-based learning and for valuable discussions in general. In addition, we thank Dr.  ...  Nathalie Japkowicz as well as the anonymous reviewers for their insightful comments and suggestions that helped us improve this paper.  ...  The second approach aims to optimize more than one metric, either by replacing the learning metric of an existing algorithm with a multi-criteria metric, or by developing a new algorithm that optimizes  ... 
doi:10.1137/1.9781611972795.80 dblp:conf/sdm/LavessonD09 fatcat:454hpthjkrhbven2zq7qa3gyme

Software Defect Prediction Using Ensemble Learning: An ANP Based Evaluation Method

Abdullateef O Balogun, Amos O Bajeh, Victor A Orie, Ayisat W Yusuf-Asaju
2018 FUOYE Journal of Engineering and Technology  
In essence, it is valid to say that before deciding which model or classifier is better for software defect prediction, all performance metrics should be considered.Keywords— Data mining, Machine Learning  ...  Network Process (ANP) multi-criteria decision method.  ...  ACKNOWLEDGMENT The authors wish to thank the reviewers of this article for their comments and corrections.  ... 
doi:10.46792/fuoyejet.v3i2.200 fatcat:3b2eaocmkfa3nnuqkek7sxptce

Combining evolutionary algorithms and exact approaches for multi-objective knowledge discovery

Mohammed Khabzaoui, Clarisse Dhaenens, El-Ghazali Talbi
2008 Reserche operationelle  
An important task of knowledge discovery deals with discovering association rules. This very general model has been widely studied and efficient algorithms have been proposed.  ...  But most of the time, only frequent rules are seeked.  ...  In this section we propose to study the opportunity of developing exact methods for the multi-criteria rule mining problem and discuss of their limitations.  ... 
doi:10.1051/ro:2008004 fatcat:g536abir5zd3xf7cwa3bqsxlpa

A method for evaluation of learning components

Niklas Lavesson, Veselka Boeva, Elena Tsiporkova, Paul Davidsson
2013 Automated Software Engineering : An International Journal  
The method provides a common ground for different stakeholders and enables a multi-expert and multi-criteria evaluation of machine learning algorithms prior to inclusion in software products.  ...  It is difficult to identify suitable learning algorithms for a particular task and software product because the non-functional requirements of the product affect algorithm suitability.  ...  For example, Nakhaeizadeh and Schnabl (1997) present a multi-criteria metric for learning algorithm evaluation and define the efficiency of an algorithm as its weighted positive properties (for example  ... 
doi:10.1007/s10515-013-0123-1 fatcat:gjclaxmgxvhntlufdvcuwiyjam

A hybrid agent based virtual organization for studying knowledge evolution in social systems

Sujatha Srinivasan, Sivakumar Ramakrishnan
2012 Artificial intelligence research  
CA's have been used for modeling the evolution of complex social systems, for re-engineering rule based systems, for data mining, and for solving optimization problems.  ...  The performance of the ABVO is evaluated using the number of dominators returned, the metric values of these rules represented as the objective vector and in classifying unknown test data instances.  ...  The algorithm evaluates the rules on test data, presents the rules and rule metrics and stops.  ... 
doi:10.5430/air.v1n2p99 fatcat:7d6ag7qcsraynjjqnetpbn27be

Review of Rule Quality Measurement: Metrics and Rule Evaluation Models

Munirah Muslim, E. Winarko
2018 International Journal of Computer Engineering in Research Trends  
from the experts or human experts as well as those resulting from the induction rule algorithm much developed.  ...  Therefore, the need for a formula that can measure the quality of the resulting rule and assess the consistency of the rule.  ...  Then, data mining has been renowned for utilizing data stored on database systems.  ... 
doi:10.22362/ijcert/2018/v5/i1/v5i102 fatcat:mrsxwnj52nfkdnjsmnsz6rdnk4

Probability of Predicting Cancer in Patient by Analyzing Risk Factors

Pallavi Mirajkar, Dr. G. Prasanna Lakshmi
2017 IOSR Journal of Computer Engineering  
One of the applications of analytical hierarchy process is medical diagnosis which is mostly used in research area. Many researchers are focusing on medical field.  ...  This study introduces an approach to find out risk level of the cancer based on analytical hierarchy process (AHP). Cancer is the most frequent cause of death.  ...  ) technique in data mining.  ... 
doi:10.9790/0661-1902013338 fatcat:ejsq5cd7jnalni7tn6wijref5y

APPrOVE: Application-oriented validation and evaluation of supervised learners

Niklas Lavesson, Paul Davidsson
2010 2010 5th IEEE International Conference Intelligent Systems  
One study presents a multi-criteria metric for learning algorithm evaluation [8] and define the efficiency of an algorithm as its weighted positive properties (for example, understandability) divided  ...  IV -CRITERIA EVALUATION RESULTS Normalized metric scores for each pair of quality attribute and algorithm as well as CEF evaluation scores for each algorithm.  ... 
doi:10.1109/is.2010.5548402 dblp:conf/is/LavessonD10 fatcat:vhlzueg545du3ifscz3zgd73oa

Unifying The Evaluation Criteria Of Many Objectives Optimization Using Fuzzy Delphi Method

Rawia Tahrir Mohammed, Razali Yaakob, Nurfadhlina Mohd Sharef, Rusli Abdullah
2021 Baghdad Science Journal  
Thus, unify a set of most suitable evaluation criteria of the MaOO is needed. This study proposed a distinct unifying model for the MaOO evaluation criteria using the fuzzy Delphi method.  ...  Although many evaluation criteria are available, yet most of the evaluation and benchmarking of the MaOO with state-of-art algorithms perform using one or two performance indicators without clear evidence  ...  As present in the methodology section, the process of developing an evaluation criteria model comprises three steps: (1) Identify the evaluation criteria for MaOO: In this section, all criteria,  ... 
doi:10.21123/bsj.2021.18.4(suppl.).1423 fatcat:5rstcaeyxvcllhoolsslsab7ne

MO-Miner: A Data Mining Tool Based on Multi-Objective Genetic Algorithms [chapter]

Gina M. B. de Oliveira, Luiz G. A. Martins, Maria C. S. Takiguti
2008 Advances in Robotics, Automation and Control  
Mining Tool Based on Multi-Objective Genetic Algorithms MO-Miner: A Data Mining Tool Based on Multi-Objective Genetic Algorithms www.intechopen.com  ...  Different paths related to multi-objective genetic algorithms and data mining can be explored as continuity of this study, such as: inclusion of other metrics as comprehensibility (Freitas, 2002) ; use  ...  Through this book, we also find navigation and vision algorithms, automatic handwritten comprehension and speech recognition systems that will be included in the next generation of productive systems developed  ... 
doi:10.5772/5522 fatcat:ygmhckebnrfrlmddk4vja4pvom

A Survey of Quantification of Privacy Preserving Data Mining Algorithms [chapter]

Elisa Bertino, Dan Lin, Wei Jiang
2008 Privacy-Preserving Data Mining  
An important aspect in the design of such algorithms is the identification of suitable evaluation criteria and the development of related benchmarks.  ...  The aim of privacy preserving data mining (PPDM) algorithms is to extract relevant knowledge from large amounts of data while protecting at the same time sensitive information.  ...  For a better understanding of PPDM related metrics, we next identify a proper set of criteria and the related benchmarks for evaluating PPDM algorithms.  ... 
doi:10.1007/978-0-387-70992-5_8 dblp:series/ads/BertinoLJ08 fatcat:4fzwaydohrbjff2xyhqzqasouy

Privacy Preserving Data Mining Algorithms by Data Distortion

Wu Xiao-dan, Yue Dian-min, Liu Feng-li, Wang Yun-feng, Chu Chao-Hsien
2006 2006 International Conference on Management Science and Engineering  
Recently, a new class of data mining methods, known as privacy preserving data mining (PPDM) algorithms, has been developed by the research community working on security and knowledge discovery.  ...  A set of metrics and a theoretical framework are also proposed for assessing the relative performance of selected PPDM algorithms. Finally, we share directions for future research.  ...  Evaluation criteria An important aspect in the development and assessment of algorithms and tools, for privacy preserving data mining is the identification of suitable evaluation criteria and the development  ... 
doi:10.1109/icmse.2006.313871 fatcat:ygfadpganraurbi7ev7zmtyhzu

Conformance checking

Sebastian Dunzer, Matthias Stierle, Martin Matzner, Stephan Baier
2019 Proceedings of the 11th International Conference on Subject-Oriented Business Process Management - S-BPM ONE '19  
Conformance checking is a set of process mining functions that compare process instances with a given process model.  ...  Especially in the context of analyzing compliance in organizations, it is currently gaining momentum -- e.g. for auditors.  ...  If an article does not match one of the mentioned criteria it was excluded from the set of relevant literature. For the evaluation of bibliometrics, we used Scopus' Cited by number.  ... 
doi:10.1145/3329007.3329014 dblp:conf/s-bpm-one/DunzerSMB19 fatcat:cyfmzukjefa4fjyp5bdmxwalya
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