Search Results - (( code classification mining algorithm ) OR ( label classification mining algorithm ))

Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer by Tuerxun, Adilijiang

“…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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Multi-label learning based on positive label correlations using predictive apriori by Al Azaidah, Raed Hasan Saleh

“…Multi-label Learning (MLL) is a general task in data mining that consists of three main tasks: classification, label ranking, and multi-label ranking. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

“…In the second part of the study, a novel classification algorithm called Hessian semi-supervised ELM (HSS-ELM) is proposed to enhance the semi-supervised learning of ELM. …”
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Improvement anomaly intrusion detection using Fuzzy-ART based on K-means based on SNC Labeling by Zulaiha Ali Othman, Afaf Muftah Adabashi, Suhaila Zainudin, Saadat M. Al Hashmi

“…This paper presents our work to improve the performance of anomaly intrusion detection using Fuzzy-ART based on the K-means algorithm. The K-means is a modified version of the standard K-means by initializing the value K from the value obtained after data mining using Fuzzy-ART and SNC labeling technique. …”
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Feature Selection with Harmony Search for Classification: A Review by Norfadzlan, Yusup, Azlan, Mohd Zain, Nur Fatin Liyana, Mohd Rosely, Suhaila Mohamad, Yusuf

“…A good classification accuracy can be achieved when the model correctly predicted the class labels. …”
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Application of Optimization Methods for Solving Clustering and Classification Problems by Shabanzadeh, Parvaneh

“…Cluster and classification analysis are very interesting data mining topics that can be applied in many fields. …”
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Predicting game-induced emotions using EEG, data mining and machine learning by Min, Xuan Lim, Jason Teo

“…The 20 experiment cases’ results from subject-based experiments supported that the SVM classifer could accurately classify the 4 emotion states with a kappa value over 0.62, demonstrating the SVM-based algorithm’s capabilities in precisely determining the emotion label for each participant’s EEG features’ instance. …”
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Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd by Nur Farahaina, Idris

“…Classification is a data mining technique used to classify varied data types according to a specific criterion. …”
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Comparative analysis for topic classification in juz Al-Baqarah by Rahman, Mohamad Izzuddin, Samsudin, Noor Azah, Mustapha, Aida, Abdullahi Oyekunle, Adeleke

“…The SVM performance is then compared against other classification algorithms such as Naive Bayes, J48 Decision Tree and K-Nearest Neighbours. …”
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Classification of metamorphic virus using n-grams signatures by A Hamid, Isredza Rahmi, Md Sani, Nur Sakinah, Abdullah, Zubaile, Mohd Foozy, Cik Feresa, Kipli, Kuryati

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

“…No EEG studies in Malaysia has been done on school children to study their emotional behaviour while learning. Classification and prediction are the functions provided by the data mining techniques that suit in EEG signal processing. …”
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A coherent knowledge-driven deep learning model for idiomatic - aware sentiment analysis of unstructured text using Bert transformer by Bashar M. A., Tahayna

“…Machine learning and deep neural networks have shown promise in accurately representing and classifying sentiment, but they require large amounts of labeled data to train the models. In this context, the proposed novel strategy aims to eliminate the need for human labeling of the idiomatic lexicon and fine-tuning the classifier to handle the sentiment classification of tweets containing idiomatic expressions. …”
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Cyber parental control framework for objectionable web content classification and filtering based on topic modelling using enhanced latent dirichlet allocation / Hamza H. M. Altart... by Hamza H. M. , Altarturi

“…Despite substantial advancements in automating web classification that combines web mining and content classification methods, the study identifies a gap in applying advanced machine learning algorithms for superior objectionable web content classification. …”
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Prediction of ADHD from a small dataset using an adaptive EEG theta/beta ratio and PCA feature extraction by Sase, Takumi, Othman, Marini

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Prediction of ADHD from a small dataset using an adaptive EEG Theta/Beta Ratio and PCA feature extraction by Sase, Takumi, Othman, Marini

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An enhanced android botnet detection approach using feature refinement by Anwar, Shahid

“…The experimental and statistical tests show that 97.28% accuracy achieved by Random Forest machine classifier, it performs well as compared to other classification algorithms. Based on the test results, various open research issues which need to be addressed in future studies are highlighted.…”
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