Random Walk From Different Perspective

Seah, Choon Sen; Kasim, Shahreen; Fudzee, Mohd Farhan Md; Abdullah, Rusli; Atan, Rodziah

doi:10.26480/aem.02.2017.26.27

Cited by 6 publications

(2 citation statements)

References 7 publications

(8 reference statements)

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“…Data mining has been useful to extract useful information from raw data, thus help researchers decide its result [3]. One of the popular data mining techniques is Support vector machines (SVMs), which is useful to extract high dimensional data [4].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Attribute Selection and Classification Algorithm Applied to Hepatitis Patients

Samsuddin

Shah

Saedudin

et al. 2019

International Journal on Advanced Science, Engineering and Information Technology

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Data mining techniques are widely used in classification, attribute selection and prediction in the field of bioinformatics because it helps to discover meaningful new correlations, patterns and trends by sifting through large volume of data, using pattern recognition technologies as well as statistical and mathematical techniques. Hepatitis is one of the most important health problem in the world. Many studies have been performed in the diagnosis of hepatitis disease but medical diagnosis is quite difficult and visual task which is mostly done by doctors. Therefore, this research is conducted to analyse the attribute selection and classification algorithm that applied to hepatitis patients. In order to achieve goals, WEKA tool is used to conduct the experiment with different attribute selector and classification algorithm . Hepatitis dataset that are used is taken from UC Irvine repository. This research deals with various attribute selector namely CfsSubsetEval, WrapperSubsetEval, GainRatioSubsetEval and CorrelationAttributeEval. The classification algorithm that used in this research are NaiveBayesUpdatable, SMO, KStar, RandomTree and SimpleLogistic. The results of the classification model are time and accuracy. Finally, it concludes that the best attribute selector is CfsSubsetEval while the best classifier is given to SMO because SMO performance is better than other classification techniques for hepatitis patients.

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Section: Introductionmentioning

confidence: 99%

Analysis of Attribute Selection and Classification Algorithm Applied to Hepatitis Patients

Samsuddin

Shah

Saedudin

et al. 2019

International Journal on Advanced Science, Engineering and Information Technology

Self Cite

View full text Add to dashboard Cite

show abstract

“…Complementary base pairing between the sample cell and gene sequences on the chip produces different colours based on the expression level of the gene. The introduction of microarray technology allows researchers to analyse thousands of gene expression profiles simultaneously [2][3][4][5]. The datasets produced by microarray technology is known as gene expression dataset [2].…”

Section: Introductionmentioning

confidence: 99%

An Effective Pre-Processing Phase for Gene Expression Classification

Seah¹,

Kasim²,

Fudzee³

et al. 2018

IJEECS

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A raw dataset prepared by researchers comes with a lot of information. Whether the information is usefull or not, completely depends on the requirement and purposes. In machine learning, data pre-processing is the very initial stage. It is a must to make sure the dataset is totally suitable for the requirement. In significant directed random walk (sDRW), there are three steps in data pre-processing stage. First, we remove unwanted attributes, missing value and proper arrangement, followed by normalization of the expression value and lastly, filtering method is applied. The first two steps are completed by Bioconductor package while the last step is works in sDRW.

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RETRACTED ARTICLE: Significant directed walk framework to increase the accuracy of cancer classification using gene expression data

Seah

Kasim

Fudzee

et al. 2020

J Ambient Intell Human Comput

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Random Walk From Different Perspective

Abstract: This paper is presented to expose the different perspective of random walk. Random walk is applied in many different fields for prediction purposes and hence, it was further developed to improve the accuracy of prediction.

Cited by 6 publications

References 7 publications

Analysis of Attribute Selection and Classification Algorithm Applied to Hepatitis Patients

Analysis of Attribute Selection and Classification Algorithm Applied to Hepatitis Patients

An Effective Pre-Processing Phase for Gene Expression Classification

RETRACTED ARTICLE: Significant directed walk framework to increase the accuracy of cancer classification using gene expression data

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