Search Results - (( using function based algorithm ) OR ( learning classification rules algorithm ))
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New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…Classification rules were generated based on the best reduct. …”
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On equivalence of FIS and ELM for interpretable rule-based knowledge representation
Published 2023“…Classification (of information); Computer aided diagnosis; Fault detection; Fuzzy systems; Knowledge acquisition; Knowledge representation; Learning systems; Matrix algebra; Membership functions; Pattern recognition; Extreme learning machine; Fault detection and diagnosis; Fuzzy if-then rules; Fuzzy inference systems; Fuzzy membership function; Initialization technique; Interpretable rules; Rule based; Fuzzy inference; algorithm; artificial intelligence; artificial neural network; benchmarking; classification; electric power plant; factual database; feedback system; fuzzy logic; machine learning; nerve cell; reproducibility; statistical model; Algorithms; Artificial Intelligence; Benchmarking; Classification; Databases, Factual; Feedback; Fuzzy Logic; Machine Learning; Models, Statistical; Neural Networks (Computer); Neurons; Power Plants; Reproducibility of Results…”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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4
Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool
Published 2018“…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%). …”
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5
A framework of modified adaptive neuro-fuzzy inference engine
Published 2012“…The Takagi-Sugeno-Kang (TSK) type fuzzy inference system was chosen and constructed by an automatic generation of clusters as well as membership functions and minimal rules through the use of hybrid fuzzy clustering and the modified apriori algorithms respectively. …”
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6
A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition
Published 2002“…In this thesis rough sets approach was used in the preprocessing stages, namely in the vector quantization operation in which feature vectors are quantized or classified to a finite set of codebook classes. Classification rules were generated from training feature vectors set, and a modified form of the standard voter classification algorithm, that use the rough sets generated rules, was applied. …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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8
Application Of Neural Network In Malaria Parasites Classification
Published 2006“…Multilayer Perceptron (MLP) network and Radial Basis Function (RBF) network will be developed using MATLAB in which MLP network is trained with Back Propagation, Bayesian Rule and Levenberg-Marquardt learning algorithm and RBF network is trained with k-means clustering algorithm. …”
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Handgrip strength evaluation using neuro fuzzy approach
Published 2010“…The expert rules define the membership function for the fuzzy system. …”
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An interpretable fuzzy-ensemble method for classification and data analysis / Adel Lahsasna
Published 2016“…For the ensemble method, we propose a design that combines five different base classifiers and use a GA-based selection method to select a subset from all the ensemble outputs using accuracy and diversity measures as two objectives in the fitness function. …”
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12
Named entity recognition using a new fuzzy support vector machine.
Published 2008“…Nowadays more researchers use three type of approaches namely, Rule-base NER, Machine Learning-base NER and Hybrid NER to identify names. …”
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Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224)
“…Next, the weighted and transformed features were used to train Linear Discriminant Function (LDA) and to evaluate the constructed rule. …”
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Fuzzy-based classifier design for determining the eye movement data as an input reference in wheelchair motion control
Published 2015“…Since membership functions (MFs) are generated automatically, the proposed fuzzy learning algorithm can be viewed as a knowledge acquisition tool for classification problems. …”
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Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition
Published 2004“…The neural network learns the rough set’s upper and lower approximations as feature extractors simultaneously with classification. …”
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A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules
Published 2013“…Previous studies have shown that ACO is a promising machine learning technique to generate classification rules. …”
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An Artificial Intelligence-Based Knowledge Management System for Outcome-Based Education Implementing in Higher Education Institutions
Published 2025“…Recommendation system on learning analysis was implemented in a hybrid algorithm combines Rule-based and Content-based filtering algorithms. …”
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Hybrid ant colony optimization and genetic algorithm for rule induction
Published 2020“…In our proposed hybrid ACO/GA algorithm, the ACO is responsible for generating classification rules and the GA improves the classification rules iteratively using the principles of multi-neighborhood structure (i.e., mutation and crossover) procedures to overcome the local optima problem. …”
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Automatic email classification system / Phang Siew Ting
Published 2003“…For this purpose, several Machine Learning algorithms has been purposed to automate the classification of emails. …”
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20
Improved GART neural network model for pattern classification and rule extraction with application to power systems
Published 2023Subjects:Article
