Search Results - (( evolution classification mining algorithm ) OR ( program validation learning algorithm ))
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1
Classification of Immunosignature Using Random Forests for Cancer Diagnosis
Published 2015“…To attain this essential research purpose, a minimum set of genes that can assure higher performance in classification using data mining algorithms need to be detected. …”
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Proceeding Paper -
2
Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…The proposed algorithm is grounded on the two famous metaheuristic algorithms: cuckoo search (CS) and covariance matrix adaptation evolution strategy (CMA-es). …”
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3
Classification with degree of importance of attributes for stock market data mining
Published 2004“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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Article -
4
Y-type Random 2-satisfiability In Discrete Hopfield Neural Network
Published 2024“…Additionally, the proposed Hybrid Differential Evolution Algorithm was implemented into the training phase to ensure that the cost function of the Discrete Hopfield Neural Network is minimized. …”
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5
Logic mining method via hybrid discrete hopfield neural network
Published 2025“…Despite the success, the limitations of existing logic mining methods are often overlooked, hindering the search for optimal solutions in binary classification tasks. …”
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6
Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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7
Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat
Published 2022“…There is also growing interest in modeling machine learning and deep learning algorithms that can learn from user’s data, understand and react to that individual’s affective state. …”
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8
Application of data mining techniques for economic evaluation of air pollution impact and control
Published 2007“…For that purpose, we use data mining techniques. Data mining techniques applied in this thesis were: 1) Group method of data handling (GMDH), originally from engineering, introducing principles of evolution - inheritance, mutation and selection - for generating a network structure systematically to develop the automatic model, synthesis, and its validation; 2) The weighted least square (WLS) and step wise regression were also applied for some cases; 3) The classification-based association rules were applied. …”
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9
Case Slicing Technique for Feature Selection
Published 2004“…The classification accuracy obtained from the CST method is compared to other selected classification methods such as Value Difference Metric (VDM), Pre-Category Feature Importance (PCF), Cross-Category Feature Importance (CCF), Instance-Based Algorithm (IB4), Decision Tree Algorithms such as Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5), Rough Set methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) and Neural Network methods such as the Multilayer method.…”
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10
A multi-depot vehicle routing problem with stochastic road capacity and reduced two-stage stochastic integer linear programming models for rollout algorithm
Published 2021“…The results obtained from the resulting rollout policy with CPLEX execution during rollout are also presented to validate the reduced model and the matheuristic algorithm. …”
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Article -
11
System identification using Extended Kalman Filter
Published 2017“…In order to evaluate the performance of the EKF learning algorithm, the proposed algorithm validation were analyzed using model validation methods as a checker such as One Step Ahead (OSA) and correlation coefficient (R2). …”
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Student Project -
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Differential evolution for neural networks learning enhancement
Published 2008“…Three programs have developed; Differential Evolution Neural Network (DENN), Genetic Algorithm Neural Network (GANN) and Particle Swarm Optimization with Neural Network (PSONN) to probe the impact of these methods on ANN learning using various datasets. …”
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14
Mobile app of mood prediction based on menstrual cycle using machine learning algorithm / Nur Hazirah Amir
Published 2019“…It implemented Supervised Learning algorithm with Bayes’ Theorem model for the calculation of mood prediction using Python programming language. …”
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15
Predicting Student Performance in Object Oriented Programming Using Decision Tree : A Case at Kolej Poly-Tech Mara, Kuantan
Published 2013“…Using 10-fold cross validation for each algorithm, it was found that decision tree was the best algorithm with 83.6944% correctness. …”
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Conference or Workshop Item -
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Current applications of machine learning in dentistry
Published 2022“…The process is similar to a human expert that can learn by repeated training (Hung et al., 2019). The quality of the output depends on the quality of data used to train and validate the algorithm (Rowe, 2019). …”
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Book Chapter -
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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms
Published 2017“…The first proposed approach is a multi-objective fuzzy linear programming optimization (MFLP) algorithm to solve the MOOPF problem. …”
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18
Construction Noise Prediction Using Stochastic Deep Learning
Published 2022“…The programming algorithm of stochastic modelling was executed in MATLAB, whereas the deep learning model was established by using Python 3.6 programming language in Spyder. …”
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Final Year Project / Dissertation / Thesis -
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AI recommendation penetration testing tool for cross-site scripting: support vector machine algorithm
Published 2025“…The SVM algorithm, a supervised learning model, plays a crucial role in improving the efficiency of tool selection, ultimately enhancing the speed and adaptability of vulnerability detection processes. …”
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Article -
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Face recognition using eigenfaces and smooth support vector machine
Published 2011“…Support Vector Machine (SVM) is a new algorithm of data mining technique, recently received increasing popularity in machine learning community. …”
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Thesis
