Optimized Neural Network for Big Data Classification Using MapReduce Approach

2021 ◽  
pp. 429-437
Author(s):  
Sridhar Gujjeti ◽  
Suresh Pabboju
Keyword(s):  
Neural Network ◽  
Big Data ◽  
Data Classification ◽  
Big Data Classification

WOA + BRNN: An imbalanced big data classification framework using Whale optimization and deep neural network

2019 ◽  
Vol 24 (8) ◽  
pp. 5573-5592 ◽  
Author(s):  
Eslam. M. Hassib ◽  
Ali. I. El-Desouky ◽  
Labib. M. Labib ◽  
El-Sayed M. El-kenawy
Keyword(s):  
Neural Network ◽  
Big Data ◽  
Deep Neural Network ◽  
Data Classification ◽  
Classification Framework ◽  
Whale Optimization ◽  
Big Data Classification

Literature review and analysis on big data stream classification techniques

2020 ◽  
Vol 24 (3) ◽  
pp. 205-215
Author(s):  
B. Srivani ◽  
N. Sandhya ◽  
B. Padmaja Rani
Keyword(s):  
Neural Network ◽  
Big Data ◽  
Deep Learning ◽  
Data Classification ◽  
Support Vector ◽  
Complex Data ◽  
Learning Approaches ◽  
K Nearest Neighbor ◽  
Data Stream Classification ◽  
Big Data Classification

Rapid growth in technology and information lead the human to witness the improved growth in velocity, volume of data, and variety. The data in the business organizations demonstrate the development of big data applications. Because of the improving demand of applications, analysis of sophisticated streaming big data tends to become a significant area in data mining. One of the significant aspects of the research is employing deep learning approaches for effective extraction of complex data representations. Accordingly, this survey provides the detailed review of big data classification methodologies, like deep learning based techniques, Convolutional Neural Network (CNN) based techniques, K-Nearest Neighbor (KNN) based techniques, Neural Network (NN) based techniques, fuzzy based techniques, and Support vector based techniques, and so on. Moreover, a detailed study is made by concerning the parameters, like evaluation metrics, implementation tool, employed framework, datasets utilized, adopted classification methods, and accuracy range obtained by various techniques. Eventually, the research gaps and issues of various big data classification schemes are presented.

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