Evaluation on rapid profiling with clustering algorithms for plantation stocks on Bursa Malaysia
Building a stock portfolio often requires extensive financial knowledge and Herculean efforts looking at the amount of financial data to analyse. In this study, we utilized Expectation Maximization (EM), K-Means (KM), and Hierarchical Clustering (HC) algorithms to cluster the 38 plantation stocks l...
Main Authors: | Keng, Hoong Ng, Kok, Chin Khor |
---|---|
Format: | Article |
Language: | English |
Published: |
Universiti Utara Malaysia Press
2016
|
Subjects: | |
Online Access: | https://repo.uum.edu.my/id/eprint/24069/1/JICT%2015%202%202016%20%2063%E2%80%9384.pdf |
Similar Items
-
EVALUATION ON RAPID PROFILING WITH CLUSTERING ALGORITHMS FOR PLANTATION STOCKS ON BURSA MALAYSIA
by: Keng Hoong Ng, et al.
Published: (2016-11-01) -
Stock prediction by applying hybrid Clustering-GWO-NARX neural network technique
by: Das, Debashish, et al.
Published: (2017) -
Hybrid clustering-GWO-NARX neural network technique in predicting stock price
by: Das, Debashish, et al.
Published: (2017) -
Comparison of MCDM methods for intercrop selection in rubber plantations
by: Srisawat, Chutiphon, et al.
Published: (2016) -
Determining number of clusters using firefly algorithm with cluster merging for text clustering
by: Mohammed, Athraa Jasim, et al.
Published: (2015)