Search Results - (( model evaluation a algorithm ) OR ( based classification clustering algorithm ))*

Combining cluster quality index and supervised learning to predict students’ academic performance by Suhaila Zainudin, Rapi’ah Ibrahim, Hafiz Mohd Sarim

“…First, the approach performed clustering with K-Means algorithm to identifies different student groups. …”
Get full text
Get full text
Get full text

An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding by Safa, Soodabeh, Khalid, Fatimah

“…Classic bag of visual words algorithm is based on k-means clustering and every SIFT features belongs to one cluster and it leads to decreasing classification results. …”
Get full text
Get full text
Get full text

An analysis of fuzzy clustering algortihms for suggestion of supervisor and examiner of thesis title by Suhaimi, Azrina

“…Document is represented using the Vector Space Model. The index terms are then clustered using Fuzzy clustering algorithms based on similarity. …”
Get full text
Get full text

A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. …”
Get full text
Get full text

Reducing false alarm using hybrid Intrusion Detection based on X-Means clustering and Random Forest classification by Juma, Sundus, Muda, Zaiton, Yassin, Warusia

“…Unluckily, an essential provocation of this method is to maximize accuracy, detection whereas minimize false alarm rate. This paper proposed a hybrid machine learning approach based on X-Means clustering and Random Forest classification called XM-RF in order to aforementioned drawbacks. …”
Get full text
Get full text

Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

“…For segmentation, the first proposed algorithm is based on the boundary condition model, which is tested over the ISIC dataset and achieved 96% of accuracy. …”
Get full text
Get full text
Get full text
Get full text

Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms by Choong, Chun Sern

“…The best position that could achieve a classification accuracy of 93.30% through the validation process for position five (5) in the systematic model that is the centre of the pallet box. …”
Get full text
Get full text

Intelligent Color Vision System For Ripeness Classification Of Oil Palm Fresh Fruit Bunch by Fadilah, Norasyikin

“…Then, the color features of the fruit region are extracted from the images and used as inputs to an Artificial Neural Network (ANN) model learning algorithm.…”
Get full text
Get full text

A machine learning approach of predicting high potential archers by means of physical fitness indicators by Musa, Rabiu Muazu, Anwar, P. P. Abdul Majeed, Zahari, Taha

“…Hierarchical agglomerative cluster analysis (HACA) was used to cluster the archers based on the significant variables identified. k-NN model variations, i.e., fine, medium, coarse, cosine, cubic and weighted functions as well as logistic regression, were trained based on the significant performance variables. …”
Get full text
Get full text
Get full text

A machine learning approach of predicting high potential archers by means of physical fitness indicators by Muazu Musa, Rabiu, Abdul Majeed, Anwar P.P., Taha, Zahari, Chang, Siow Wee, Ab. Nasir, Ahmad Fakhri, Abdullah, Mohamad Razali

“…Hierarchical agglomerative cluster analysis (HACA) was used to cluster the archers based on the significant variables identified. k-NN model variations, i.e., fine, medium, coarse, cosine, cubic and weighted functions as well as logistic regression, were trained based on the significant performance variables. …”
Get full text
Get full text

An effective and novel wavelet neural network approach in classifying type 2 diabetics by Zainuddin, Zarita, Pauline, Ong

“…In this paper, we propose a novel enhanced fuzzy c-means clustering algorithm – specifically, the modified point symmetry-based fuzzy c-means (MPSDFCM) algorithm – in initializing the translation vectors of the WNNs. …”
Get full text
Get full text
Get full text

Unsupervised classification of multi-class chart images: A comparison of customized CNNs and transfer learning techniques by Hassan Zaidi, Syed Muhammad, Jamil Alsayaydeh, Jamil Abedalrahim, Khan, Abdul Hafeez, Khan, Abdullah Ayub, AlZubi, Ahmad Ali, Ogunshola, Benny, Herawan, Safarudin Gazali

“…By integrating transfer learning with clustering and CNN-based architecture, this study presents a robust and scalable framework for unsupervised chart image classification.…”
Get full text
Get full text
Get full text

Novel techniques for enhancement and segmentation of acne vulgaris lesions by Malik, A. S., Humayun, J., Kamel, N., Yap, F. B.-B.

“…Then, segmentation is performed by clustering the pixels based on Mahalanobis distance of each pixel from spectral models of acne vulgaris lesions. …”
Get full text
Get full text
Get full text

Topic modelling analysis of depression therapy text: a preliminary study / Teh Faradilla Abdul Rahman ... [et al.] by Abdul Rahman, Teh Faradilla, Mohd Said, Raudzatul Fathiyah, Buja, Alya Geogiana, Mat Nayan, Norshita

Get full text
Get full text

Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui by Yang , Dong Rui

“…However, unsatisfactory accuracy, slow learning speed, and stability is still a problem. In this study, we have purposed a model named as Optimized Reduced Kernel Extreme Learning Machine (Opt RKELM). …”
Get full text
Get full text
Get full text

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

“…In cluster labelling process, a cluster labelling algorithm based on calculation of minimum-distance (MD) between cluster mean and class mean was developed to label the clusters. …”
Get full text
Get full text

Relationship between psycho-maturity and performance of sepak takraw by Abdullah, Prof. Madya Dr. Mohamad Razali

“…The correlation between psycho-maturity towards the performance of sepak takraw players is evaluated in this chapter. The Louvain clustering algorithm is used to categorise the players to high, medium and low psycho-matured players based on seven fundamental psychological measures, viz. maturity status, selftalk, activation, imagery, emotion control, automaticity and goal setting. …”
Get full text
Get full text

Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

“…The descriptive analysis examines purchasing behavior through correlation and regression analyses, while the predictive model uses decision trees (J48, Random Tree, REPTree), rule-based algorithms (JRip, OneR, PART), and clustering (K-Means) to identify patterns and predict trends. …”
Get full text
Get full text

Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

“…In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
Get full text
Get full text
Get full text

Aco-based feature selection algorithm for classification by Al-mazini, Hassan Fouad Abbas

“…The modified graph clustering ant colony optimisation (MGCACO) algorithm is an effective FS method that was developed based on grouping the highly correlated features. …”
Get full text
Get full text