A Comparative Study of Famous Classification Techniques and Data Mining Tools

2019 ◽  
pp. 627-644
Author(s):  
Yash Paul ◽  
Neerendra Kumar
Keyword(s):  
Data Mining ◽  
Comparative Study ◽  
Classification Techniques ◽  
Mining Tools

Classification Techniques and Data Mining Tools Used in Medical Bioinformatics

2019 ◽  
pp. 105-126
Author(s):  
Satish Kumar David ◽  
Amr T. M. Saeb ◽  
Mohamed Rafiullah ◽  
Khalid Rubeaan
Keyword(s):  
Data Mining ◽  
Genomic Analysis ◽  
Resistance Pattern ◽  
Medical Applications ◽  
Classification Analysis ◽  
Classification Techniques ◽  
Data Mining Techniques ◽  
Use Of Data ◽  
Drug Resistance Pattern ◽  
Mining Tools

Increasing volumes of data with the increased availability information mandates the use of data mining techniques in order to gather useful information from the datasets. In this chapter, data mining techniques are described with a special emphasis on classification techniques as one important supervised learning technique. Bioinformatics tools in the field for medical applications especially in medical microbiology are discussed. This chapter presents WEKA software as a tool of choice to perform classification analysis for different kinds of available data. Uses of WEKA data mining tools for biological applications such as genomic analysis and for medical applications such as diabetes are discussed. Data mining offers novel tools for medical applications for infectious diseases; it can help in identifying the pathogen and analyzing the drug resistance pattern. For non-communicable diseases such as diabetes, it provides excellent data analysis options for analyzing large volumes of data from many clinical studies.

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