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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

“…The advantage of the cluster labelling algorithm compared to co-spectral plot and maximum-likelihood classifier was the algorithm provided a rapid production of high accuracy classification map.…”
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Comparative analysis of text classification algorithms for automated labelling of quranic verses by Adeleke, Abdullah, Samsudin, Noor Azah, Mustapha, Aida, Mohd Nawi, Nazri

“…In this paper, we propose to automate the labelling task of the Quranic verse using text classification algorithms. …”
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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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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

“…Whereas for supervised learning method, it requires teacher or prior data (i.e. large, prohibitive and labelled training data) during classification process which in real life, the cost of obtaining sufficient labelled training data is high. …”
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Multi label ranking based on positive pairwise correlations among labels by Alazaidah, Raed, Ahmad, Farzana Kabir, Mohsin, Mohamad

“…Multi-Label Classification (MLC) is a general type of classification that has attracted many researchers in the last few years. …”
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An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

“…This paper addresses the classification problem in machine learning focusing on predicting class labels for datasets with continuous features. …”
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An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

“…This paper addresses the classification problem in machine learning, focusing on predicting class labels for datasets with continuous features. …”
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Nearest neighbour group-based classification by Samsudin, Noor A., Bradley, Andrew P.

“…In this paper, we extend three variants of the nearest neighbour algorithm to develop a number of non-parametric group-based classification techniques. …”
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Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

“…For this reason, in this research,several auxiliary algorithms are introduced to improve the performance of the classification algorithm, namely the meta-heuristic algorithm. …”
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Fuzzy classification based on combinative algorithms with fuzzy similarity measure / Nur Amira Mat Saffie by Mat Saffie, Nur Amira

“…Furthermore, most classification algorithms, using either fuzzy or non-fuzzy approaches, produce results in the form of crisp or categorical classification outcomes. …”
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Real-time classification improvement of Indonesian sign system letters (SIBI) using K-Nearest Neighbor algorithm by Dhewa, Oktaf Agni, Utama, Safitri Yuliana, Nasuha, Aris, Gunawan, Teddy Surya, Pratama, Gilang Nugraha Putu

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Performances of machine learning algorithms for binary classification of network anomaly detection system by Nawir, M., Amir, A., Lynn, O.B., Yaakob, N., Ahmad, R.B.

“…The finding showed that AODE algorithm is performed well in term of accuracy and processing time for binary classification towards UNSW-NB15 dataset.…”
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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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Application of Optimization Methods for Solving Clustering and Classification Problems by Shabanzadeh, Parvaneh

“…Samples in the same cluster have the same label. The aim of data classification is to set up rules for the classification of some observations that the classes of data are supposed to be known. …”
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The classification of FTIR plastic bag spectra via label spreading and stacking by Almanifi, Omair Rashed Abdulwareth, Ng, Jee Kwan, Anwar P. P., Abdul Majeed

“…Four pipelines were investigated, consisting of two machine learning algorithms, a stacked model that stacks the KNN, SVM and RF algorithms together, and Label spreading, as well as two different dimensionality reduction methods namely; SVD and UMAP. …”
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EMOTION RECOGNITION USING GALVANIC SKIN RESPONSE (GSR) SIGNAL by RAMOS UKAR, YAKOBUS

“…Features and class labels can import into the Classification Learner application in MATLAB software to train and test various classifiers. …”
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Semantic shot classification in soccer videos via playfield ratio and object size considerations. by Abdul Halin, Alfian, Mohd Sharef, Nurfadhlina, Jantan, Azrul Hazri

“…This paper presents a semantic shot classification algorithm for soccer videos. Generally, each shot within a match video is assigned either a far or close up-view class label. …”
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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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Improving multi-resident activity recognition in smart home using multi label classification with adaptive profiling by Mohamed, Raihani

“…Furthermore, there is tendency that multi label classifications used instead of traditional single label classification technique. …”
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Knowledge base processing method based on text classification algorithm by Baisheng Zhong, Mohd Shamrie Sainin, Tan Soo Fun

“…The text classification algorithm's knowledge base processing method utilizes existing data from the knowledge base to guide the construction and training of the classification model. …”
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