Search Results - (( process classification rules algorithm ) OR ( using optimization based algorithm ))

A new ant based rule extraction algorithm for web classification by Ku-Mahamud, Ku Ruhana, Saian, Rizauddin

“…Using Classifier-based attribute subset selection will reduce more attributes, but sacrifice the performance of the classifier.A hybrid ant colony optimization with simulated annealing algorithm to discover rules from data is proposed.The simulated annealing technique will minimize the problem of low quality discovered rule by an ant in a colony.The best rule for a colony will then be chosen and later the best rule among the colonies will be included in the rule set.The best rule for a colony will then be chosen and later the best rule among the colonies will be included in the rule set.The rule set is arranged in decreasing order of generation.Thirteen data sets which consist of discrete and continuous data were used to evaluate the performance of the proposed algorithm in terms of accuracy, number of rules and number of terms in the rules.Experimental results obtained from the proposed algorithm are comparable to the results of the Ant-Miner algorithm in terms of rule accuracy but are better in terms of rule simplicity.…”
Get full text
Get full text
Get full text
Get full text

An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

“…The algorithms involved were Genetic Algorithm, Differential Evolution Algorithm, Particle Swarm Optimization, Butterfly Optimization Algorithm, Teaching-Learning-Based Optimization Algorithm, Harmony Search Algorithm and Gravitational Search Algorithm. …”
Get full text
Get full text

A Performance Evaluation of Chi-Square Pruning Techniques in Class Association Rules Optimization by Chern-Tong, H., Aziz, I.A.

“…To optimize the frequent itemsets based on the support value, in this research, we proposed a new optimization pruning technique to prune decision tree according to the correlation of each decision tree branches using genetic algorithm. …”
Get full text
Get full text

A Performance Evaluation of Chi-Square Pruning Techniques in Class Association Rules Optimization by Chern-Tong, H., Aziz, I.A.

“…To optimize the frequent itemsets based on the support value, in this research, we proposed a new optimization pruning technique to prune decision tree according to the correlation of each decision tree branches using genetic algorithm. …”
Get full text
Get full text

Compressing and improving fuzzy rules using genetic algorithm and its application to fault detection by Yap K.S., Wong S.Y., Tiong S.K.

Subjects:

Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi

“…Many features were explored by using a DM algorithm, which created the classification rules as a decision tree (DT) structure from the first study area. …”
Get full text
Get full text
Get full text

Optimized techniques for landslide detection and characteristics using LiDAR data by Mezaal, Mustafa Ridha

“…Also, six techniques: Ant Colony Optimization (ACO), Gain Ratio (GR), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), Random forest (RF), and Correlation-based Feature Selection (CFS) were used for the feature selection. …”
Get full text
Get full text
Get full text

Real-time oil palm fruit bunch ripeness grading system using image processing techniques by Alfatni, Meftah Salem M.

“…These results are optimal based on the thorns model. A new approach was developed using expert rules-based system. …”
Get full text
Get full text

A new fuzzy criterion-referenced assessment with a fuzzy rule selection technique and a monotonicity-preserving similarity reasoning scheme by Jee, T.L, Tay, K.M, Ng, CK

“…We formulate the process of minimizing the number of selected rules as a constrained optimization problem and a genetic algorithm (GA) technique is implemented. …”
Get full text
Get full text

Context enrichment framework for sentiment analysis in handling word ambiguity resolution by Yusof, Nor Nadiah

“…NAM is evaluated by comparing its performance with the baseline negation rule-based, through accuracy assessment using the summation approach. …”
Get full text
Get full text

A study on component-based technology for development of complex bioinformatics software by Ali Shah, Zuraini, Deris, Safaai, Othman, Muhamad Razib, Zakaria, Zalmiyah, Saad, Puteh, Hassan, Rohayanti, Muda, Mohd. Hilmi, Kasim, Shahreen, Roslan, Rosfuzah

“…Othman present a comprehensive method based on two-layer multiclass classifiers. The first layer is used to detect up to superfamily and family in SCOP hierarchy, by using optimized binary SVM classification rules directly to ROC-Area. …”
Get full text
Get full text

An enhancement of classification technique based on rough set theory for intrusion detection system application by Noor Suhana, Sulaiman

“…Thus, to deal with huge dataset, data mining technique can be improved by introducing discretization algorithm to increase classification performance. The generation of rule is considered a crucial process in data mining and the generated rules are in a huge number. …”
Get full text
Get full text

Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

“…Fuzzy modeling is a process of generating parameters which are fuzzy rule and membership function. …”
Get full text
Get full text
Get full text

DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH by LUONG, TRUNG TUAN

“…The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. …”
Get full text
Get full text

A new integrated approach for evaluating sustainable development in the electric vehicle sector by Lu, Wen Min, Chou, Chienheng, Ting, Irene Wei Kiong, Liu, Shangming

“…This study identifies the relative importance of the classification attribute variables based on the classification rules of the target attributes by conducting further analysis with the CART decision model and constructs an optimal prediction model.…”
Get full text
Get full text
Get full text
Get full text

Predicting stroke using ant colony optimization algorithm / Azfaruddin Azri and Rizauddin Saian by Azri, Azfaruddin, Saian, Rizauddin

Get full text
Get full text

Breast cancer detection by using associative classifier with rule refinement method based on relevance feedback by Abubacker, Nirase Fathima, Azman, Azreen, Doraisamy, Shyamala, Azmi Murad, Masrah Azrifah

“…Based on the validated classification result either correct or incorrect, the rules that are responsible for classification are refined in three phases. …”
Get full text
Get full text

Adaptive parameter control strategy for ant-miner classification algorithm by Al-Behadili, Hayder Naser Khraibet, Sagban, Rafid, Ku-Mahamud, Ku Ruhana

“…A key aspect of this algorithm is the selection of an appropriate number of terms to be included in the classification rule. …”
Get full text
Get full text
Get full text

Irrelevant feature and rule removal for structural associative classification by Mohd Shaharanee, Izwan Nizal, Jamil, Jastini

“…In the classification task, the presence of irrelevant features can significantly degrade the performance of classification algorithms,in terms of additional processing time, more complex models and the likelihood that the models have poor generalization power due to the over fitting problem.Practical applications of association rule mining often suffer from overwhelming number of rules that are generated, many of which are not interesting or not useful for the application in question.Removing rules comprised of irrelevant features can significantly improve the overall performance.In this paper, we explore and compare the use of a feature selection measure to filter out unnecessary and irrelevant features/attributes prior to association rules generation.The experiments are performed using a number of real-world datasets that represent diverse characteristics of data items.Empirical results confirm that by utilizing feature subset selection prior to association rule generation, a large number of rules with irrelevant features can be eliminated.More importantly, the results reveal that removing rules that hold irrelevant features improve the accuracy rate and capability to retain the rule coverage rate of structural associative association.…”
Get full text
Get full text
Get full text

Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

“…From the data analysis using WEKA software, the production rules classifier (PART) is found to be the most accurate classification algorithm in classifying the emotion which yields the highest precision percentage of 99.6% compared to J48 (99.5%) and Naïve Bayes (96.2%). …”
Get full text
Get full text