Search Results - (( pattern clustering algorithm ) OR ( patterns among algorithm ))*

Analysis of K-Mean and X-Mean Clustering Algorithms Using Ontology-Based Dataset Filtering by Rahmah, Mokhtar, Raza, Muhammad Ahsan, Fauziah, Zainuddin, Nor Azhar, Ahmad, Raza, Muhammad Fahad, Raza, Binish

“…In this paper, we have compared the performance of K-Mean and XMean clustering algorithms using two datasets of student enrollment in higher education institutions. …”
Get full text
Get full text
Get full text

Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
Get full text
Get full text
Get full text
Get full text

An efficient fuzzy C-least median clustering algorithm by Mallik, Moksud Alam, Zulkurnain, Nurul Fariza, Nizamuddin, Mohammed Khaja, Aboosalih, K C

“…In this paper we are discussing our new procedure for clustering called Fuzzy C-least median of squares algorithm which is an improvement to Fuzzy C-means (FCM) algorithm. …”
Get full text
Get full text
Get full text
Get full text

Modeling of vehicle trajectory clustering based on LCSS for traffic pattern extraction by Choong, Mei Yeen, Lorita Angeline, Chin, Renee Ka Yin, Yeo, Kiam Beng, Teo, Kenneth Tze Kin

“…The implementation of k-means and fuzzy c-means (FCM) clustering algorithm for vehicle flow analyzing task is served as focus in this paper. …”
Get full text
Get full text
Get full text
Get full text

Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman by Seman, Ali

“…Six Y-STR data sets were used as a benchmark to evaluate the performances of the algorithm against the other eight partitional clustering algorithms. …”
Get full text
Get full text

A survey: Challenges of image segmentation based fuzzy c-means clustering algorithm by Alomoush W., Alrosan A., Norwawi N., Alomari Y., Albashish D., Almomani A., Alqahtani M.

Partitional clustering algorithms for highly similar and sparseness Y-Short Tandem Repeat Data / Ali Seman by Seman, Ali

Get full text
Get full text

STATISTICAL FEATURE LEARNING THROUGH ENHANCED DELAUNAY CLUSTERING AND ENSEMBLE CLASSIFIERS FOR SKIN LESION SEGMENTATION AND CLASSIFICATION by Adil H., Khan, Dayang Nurfatimah, Awang Iskandar, Jawad F., Al-Asad, SAMIR, EL-NAKLA, SADIQ A., ALHUWAIDI

“…Moreover, skin lesion images are clustered based on fused color, pattern and shape based features. …”
Get full text
Get full text
Get full text

A framework of modified adaptive neuro-fuzzy inference engine by Hossen, Md. Jakir

“…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. …”
Get full text
Get full text

A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat by Sakamat, Norzehan

“…Size was extracted using Extreme Point Detection algorithm and Hit or Miss Transformation method was used to extract the stroke formation pattern. …”
Get full text
Get full text

Music Recommender System Using Machine Learning Content-Based Filtering Technique by Foong, Kin Hong

“…These algorithms identify hidden patterns or data groupings without the assistance of a human. …”
Get full text
Get full text

Clustering of large time-series datasets using a multi-step approach / Saeed Reza Aghabozorgi Sahaf Yazdi by Yazdi, Saeed Reza Aghabozorgi Sahaf

“…It overcomes the limitations of conventional clustering algorithms in dealing with time-series data. …”
Get full text
Get full text

Facilitating resource allocation decision through Bibliomining: the case of UTM's library / Md Razib Karno by Karno, Md Razib

“…The data mining technique was adopted to explore the relationship among statistically patterned and clustered bibliographic data. …”
Get full text
Get full text

Dietary patterns and health outcomes among African American maintenance hemodialysis patients by Tallman, Dina A., Latifi, Eno, Kaur, Deepinder, Sulaheen, Ayesha, Ikizler, T. Alp, Chinna, Karuthan, Mat Daud, Zulfitri 'Azuan, Karupaiah, Tilakavati, Khosla, Pramod

“…Implausible energy intake reports were screened out by comparing reported energy intake (rEI) with predicted total energy expenditure (pTEE). Cluster analysis, using the k-means algorithm, identified two distinct dietary patterns in the study population: a high “sugar sweetened beverage” pattern (hiSSB) and a low “sugar sweetened beverage pattern” (loSSB). …”
Get full text
Get full text
Get full text

Development and characterization of anonymous nuclear markers to determine genetic variation in two groupers species and their hybrids by Ahmad Zaidi Tani

“…Among these 13 E. lanceolatus and E. fuscoguttatus ncni-ANM loci ranged in size from 153 to 177 bp and 157 to 624 bp respectively revealing variation across all OTUs through visualization of agarose gel electrophoresis patterns and binary matrix scoring. …”
Get full text
Get full text
Get full text

Face emotion recognition using artificial intelligence techniques by Kartigayan Muthukaruppan

“…It is found, from the optimized data, that there is no common pattern to recognize emotions within among the three subjects. …”
Get full text

A Novel Pixel Counting Technique to Assess the Volumetric Changes in Human Brain Morphology by K., Nithyakalyani, R., Kalpana, S., Sudhakar, N., Vigneswaran

“…The clustering technique pursued includes the traditional K-means and fuzzy Cmeans algorithm by considering the Euclidean distance metric toward grouping of entities of similar pattern vectors. …”
Get full text
Get full text
Get full text

Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

“…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
Get full text
Get full text

Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

“…However, further study is needed in the feature extraction and clustering algorithms part as the performance of the pattern classification is still depending on the data input.…”
Get full text
Get full text

Analyzing students records to identify patterns of students' performance by Hoe A.C.K., Ahmad M.S., Hooi T.C., Shanmugam M., Gunasekaran S.S., Cob Z.C., Ramasamy A.

“…Academic failures among university students have been the subject of interest in higher education community. …”