Acharya Biswa - Academia.edu (original) (raw)
Computer Science Researcher
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Victoria University Wellington
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Papers by Acharya Biswa
IEEE Access
Medical datasets frequently include vast feature sets with numerous features that are related to ... more Medical datasets frequently include vast feature sets with numerous features that are related to one another. As a result, the curse of dimensionality affects learning from a medical dataset to discover significant characteristics, making it necessary to minimize the feature set. Feature selection (FS) is a major step in classification and also in reducing the dimension. This study attempts a novel Binary Multi-objective Chimp Optimization Algorithm (BMOChOA) with dual archive and k-nearest neighbors (KNN) classifier for mining relevant aspects from medical data. In this research, 12 versions of BMOChOA are implemented based on the group information and types of chaotic functions used. The best Pareto front obtained from suggested BMOChOA variations is compared with three benchmark multi-objective FS methods by taking 14 popular medical datasets of variable dimensions. By analyzing the experimental outputs using four multiobjective performance evaluators, it is found that the proposed FS method is superior in finding the best trade-off between the two objective functions: the number of features and classification performance.
IGI Global, 2018
The term big data refers to the data that exceeds the processing or analyzing capacity of existin... more The term big data refers to the data that exceeds the processing or analyzing capacity of existing database management systems. The inability of existing DBMS to handle big data is due to its large volume, high velocity, pertaining veracity, heterogeneous variety, and on-atomic values. Nowadays, healthcare plays a vital role in everyone's life. It becomes a very large and open platform for everyone to do all kinds of research work without affecting human life. When it comes to disease, there are so many types found all over the world. But among them, AIDS (acquired immunodeficiency syndrome) is a disease that spreads so quickly and can easily turn life to death. There are many studies going on to create drugs to cure this deadly disease, but until now, there has been no success. In cases such as this, big data is implemented for better a result, which will have a good impact on society.
— Digital world is growing in no time and become a lot of complicated within the volume (terabyte... more — Digital world is growing in no time and become a lot of complicated within the volume (terabyte to petabyte), variety (structured and un-structured and hybrid), speed (high speed in growth) in nature. This refers to as 'Big Data' that's a world development. This can be usually thought-about to be information from a knowledge of an information assortment that has fully grown thus massive it can't be effectively managed or exploited victimization standard data management tools: e.g., classic relational database management systems (RDBMS) or standard search engines. At the side of the event of the web and cloud computing, there would like knowledge bases to be able to store and method massive data effectively, demand for top performance once reading and writing, therefore the ancient computer database is facing several new challenges. Particularly in massive scale and high concurrency applications, like search engines and SNS, using the relational database to store and query dynamic user data has appeared to be inadequate. During this case, to handle this downside, ancient RDBMS are complemented by specifically designed a chic set of other DBMS; like-NoSQL, NewSQL and Search-based systemms.
IEEE Access
Medical datasets frequently include vast feature sets with numerous features that are related to ... more Medical datasets frequently include vast feature sets with numerous features that are related to one another. As a result, the curse of dimensionality affects learning from a medical dataset to discover significant characteristics, making it necessary to minimize the feature set. Feature selection (FS) is a major step in classification and also in reducing the dimension. This study attempts a novel Binary Multi-objective Chimp Optimization Algorithm (BMOChOA) with dual archive and k-nearest neighbors (KNN) classifier for mining relevant aspects from medical data. In this research, 12 versions of BMOChOA are implemented based on the group information and types of chaotic functions used. The best Pareto front obtained from suggested BMOChOA variations is compared with three benchmark multi-objective FS methods by taking 14 popular medical datasets of variable dimensions. By analyzing the experimental outputs using four multiobjective performance evaluators, it is found that the proposed FS method is superior in finding the best trade-off between the two objective functions: the number of features and classification performance.
IGI Global, 2018
The term big data refers to the data that exceeds the processing or analyzing capacity of existin... more The term big data refers to the data that exceeds the processing or analyzing capacity of existing database management systems. The inability of existing DBMS to handle big data is due to its large volume, high velocity, pertaining veracity, heterogeneous variety, and on-atomic values. Nowadays, healthcare plays a vital role in everyone's life. It becomes a very large and open platform for everyone to do all kinds of research work without affecting human life. When it comes to disease, there are so many types found all over the world. But among them, AIDS (acquired immunodeficiency syndrome) is a disease that spreads so quickly and can easily turn life to death. There are many studies going on to create drugs to cure this deadly disease, but until now, there has been no success. In cases such as this, big data is implemented for better a result, which will have a good impact on society.
— Digital world is growing in no time and become a lot of complicated within the volume (terabyte... more — Digital world is growing in no time and become a lot of complicated within the volume (terabyte to petabyte), variety (structured and un-structured and hybrid), speed (high speed in growth) in nature. This refers to as 'Big Data' that's a world development. This can be usually thought-about to be information from a knowledge of an information assortment that has fully grown thus massive it can't be effectively managed or exploited victimization standard data management tools: e.g., classic relational database management systems (RDBMS) or standard search engines. At the side of the event of the web and cloud computing, there would like knowledge bases to be able to store and method massive data effectively, demand for top performance once reading and writing, therefore the ancient computer database is facing several new challenges. Particularly in massive scale and high concurrency applications, like search engines and SNS, using the relational database to store and query dynamic user data has appeared to be inadequate. During this case, to handle this downside, ancient RDBMS are complemented by specifically designed a chic set of other DBMS; like-NoSQL, NewSQL and Search-based systemms.