Search Results - (( based constructive learning algorithm ) OR ( data classification using algorithm ))
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An efficient and effective case classification method based on slicing
Published 2006“…The paper also discusses two of common classification algorithms that are used either in data mining or in general AI. …”
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An ensemble data summarization approach based on feature transformation to learning relational data
Published 2015“…A ensemble clustering is designed, used and evaluated to generate the final classification framework that will take all input generated from the GA based clustering with Feature Selection and Feature Construction algorithms and perform the classification task for the relational datasets. …”
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An evolutionary based features construction methods for data summarization approach
Published 2015“…Here, feature construction methods are applied in order to improve the descriptive accuracy of the DARA algorithm.This research proposes novel feature construction methods, called Variable Length Feature Construction without Substitution (VLFCWOS) and Variable Length Feature Construction with Substitution(VLFCWS), in order to construct a set of relevant features in learning relational data. …”
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Multi-label learning based on positive label correlations using predictive apriori
Published 2019“…Along with that, two algorithms have been constructed by capturing the positive correlations where the first algorithm (MLR-PC) captures the positive global correlations and the second algorithm (MLCBA) proposes an adaption of AC algorithm to handle MLC based on the positive local correlations. …”
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Machine learning for data classification in construction project planning
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Sentiment analysis for malay newspaper (SAMNews) using negative selection algorithm / Nur Amalina Redzuan
Published 2013“…Sentiment Analysis for Malay Newspaper (SAMNews) is constructed using the negative selection algorithm which is able to classify the sentiment in newspaper’s sentences into the polarity (positive, negative or neutral) automatically repose on detectors word. …”
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Sentiment analysis for airline services on Twitter using deep learning with word embedding / Mawada Mohamed Nour El Daim El Khalifa
Published 2020“…The role of Sentiment Analysis (SA) is to classify people's opinions into different categories, such as positive and negative from text, using existing algorithms. However, existing approaches such as the Bag of Words (BOW) model is frequently used for text classification, where a document is mapped to a feature vector before the construction of the actual model, using machine learning techniques, like Logistical Regression and Support Vector algorithms. …”
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Classification of stock market index based on predictive fuzzy decision tree
Published 2005“…In particular, predictive FDT algorithm is based on the concept of degree of importance of attribute contributing to the classification. …”
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Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224)
“…The designed algorithm was structured in k-fold cross-validation in attempt to minimise the biasness of the classification performance, measured using error rate. …”
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Predicting game-induced emotions using EEG, data mining and machine learning
Published 2024“…The data acquisition stage, data pre-processing, data annotation and feature extraction stage were designed and conducted in this paper to obtain and extract the EEG features from the Gameemo dataset. …”
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Personalized Recommendation Classification Model of Students’ Social Well-being Based on Personality Trait Determinants Using Machine Learning Algorithms
Published 2023“…In this study, how different personality trait models compare in terms of accuracy and reliability is explored using different machine learning algorithms using the WEKA tool. …”
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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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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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Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization
Published 2021“…Hybrid combinations of feature selection, classification and visualisation using machine learning (ML) methods have the potential for enhanced understanding and 30-day mortality prediction of patients with cardiovascular disease using population-specific data. …”
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A systematic review of machine learning techniques and applications in soil improvement using green materials
Published 2023“…The current study aims to comprehensively evaluate recent breakthroughs in machine learning algorithms for soil improvement using a systematic procedure known as PRISMA and meta-analysis. …”
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Machine Learning based Predictive Modelling of Cybersecurity Threats Utilising Behavioural Data
Published 2023“…The algorithms are used to construct, test, and validate three categories of cybercrime threat (Malware, Social Engineering, and Password Attack) predictive models. …”
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An ensemble of neural network and modified grey wolf optimizer for stock prediction
Published 2019“…Widespread models like Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Evolutionary Strategy (ES) and Population-Based Incremental Learning (PBIL) dealing with the specified problems are also explored and compared. …”
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Stress mental health symptom assessment mobile application for young adults
Published 2023“…As for the panic attack prediction feature, the application will transmit user-input responses to a model previously trained using historical data. Before this stage, the KNN algorithm is employed to construct the model using Google Form response data as part of the application development process. …”
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Final Year Project / Dissertation / Thesis
