Sahraoui et al., 2001 - Google Patents
Building quality estimation models with fuzzy threshold valuesSahraoui et al., 2001
View PDF- Document ID
- 3865426713931209064
- Author
- Sahraoui H
- Boukadoum M
- Lounis H
- Publication year
- Publication venue
- L’objet
External Links
Snippet
This work presents an approach to circumvent one of the major problems with techniques to build and apply software quality estimation models, namely the use of precise metric thresholds values. We used a fuzzy logic based approach to investigate the stability of a …
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/02—Knowledge representation
- G06N5/022—Knowledge engineering, knowledge acquisition
- G06N5/025—Extracting rules from data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/04—Inference methods or devices
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N7/00—Computer systems based on specific mathematical models
- G06N7/005—Probabilistic networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F17/30705—Clustering or classification
- G06F17/3071—Clustering or classification including class or cluster creation or modification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
- G06F17/30386—Retrieval requests
- G06F17/30424—Query processing
- G06F17/30477—Query execution
- G06F17/30507—Applying rules; deductive queries
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6267—Classification techniques
- G06K9/6279—Classification techniques relating to the number of classes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US20220398460A1 (en) | Automatic xai (autoxai) with evolutionary nas techniques and model discovery and refinement | |
US20220391670A1 (en) | Explanation and interpretation generation system | |
US6647379B2 (en) | Method and apparatus for interpreting information | |
Perez et al. | Supervised classification with conditional Gaussian networks: Increasing the structure complexity from naive Bayes | |
CN118569655B (en) | Staged data life cycle safety assessment method and system | |
Tu et al. | FRUGAL: Unlocking semi-supervised learning for software analytics | |
Pauwels et al. | Detecting anomalies in hybrid business process logs | |
Nimmy et al. | Interpreting the antecedents of a predicted output by capturing the interdependencies among the system features and their evolution over time | |
Sahraoui et al. | Building quality estimation models with fuzzy threshold values | |
Sahraoui et al. | Predicting Class Libraries Interface Evolution: an investigation into machine learning approaches | |
Lounis et al. | Machine-learning techniques for software product quality assessment | |
Escovar et al. | Using Fuzzy Ontologies to Extend Semantically Similar Data Mining. | |
Magro et al. | A confirmation technique for predictive maintenance using the Rough Set Theory | |
Sahraoui et al. | Using fuzzy threshold values for predicting class libraries interface evolution | |
Sahraoui et al. | A fuzzy logic framework to improve the performance and interpretation of rule-based quality prediction models for oo software | |
Schenker et al. | The application of fuzzy enhanced case-based reasoning for identifying fault-prone modules | |
Henderson et al. | Sizing of analogue circuits for small-signal gains | |
Sahraoui et al. | Toward the automatic assessment of evolvability for reusable class libraries | |
Kumari et al. | A systematic approach towards development of universal software fault prediction model using object-oriented design measurement | |
Ioniță et al. | Intelligent system for diagnosis of a three-phase separator | |
Ibrahim et al. | CHISC-AC: Compact Highest Subset Confidence-Based Associative Classification¹ | |
Wang | Analysis of Web Mining Method Based on Intelligent E-Commerce Data | |
Khobzaoui et al. | Data mining Contribution to Intrusion Detection Systems Improvement | |
Hind et al. | Consumer-Driven Explanations for Machine Learning Decisions: An Empirical Study of Robustness | |
Ma et al. | Research on Last State Based Hidden Markov Models Encoding Algorithm |