ISSN 2394-5125
 

Research Article 


A COMPREHENSIVE ANALYSIS OF CLASSIFICATION MODELS BASED ON MACHINE AND DEEP LEARNING

ALI BADIE, MOHAMMAD AMIN MORAGHEB, ALIREZA DEHGHAN, ALI NOSHAD.

Abstract
Having examined many scientific researches, classification can perceive as one of the prominent techniques which
utilize widely in a variety of data mining modes. Acquiring insight such as efficiently of performance on large data
sets, robustness in handling variety of data sets with corrupted data, and classification ability with aim of producing
valid and new knowledge about the functionality of every classification model can exert very beneficial effects on
tasks that are addressed with machine learning users. Inspired by these problems, in the current study we introduced
a design of conditional Generative Adversarial Network–Deep Neural Network (cGAN-DNN) architecture for
classification of records from two hospital that was collected from patients affected with breast cancer and diabetes.
Our experimental results show that the model developed here, can reliably and with robust stability classify the
subjects with an accuracy of 98.0% (diabetes) and 99.6% (breast cancer). In the terms of sensitivity, precision, and
F1-score the obtained results are 98.4%, 98.5%, and 98.2% (diabetes), 99.7%, 99.4%, and 99.6% (breast cancer),
respectively. Besides, the proposed model was validated in the comparison with machine learning approaches,
which experimental results claim a high inconsistency among machine-learning based approaches. Regarding
obtained results from the experiments and evaluation based on metrics, we can demonstrate that the proposed model
can be tuned to utilize into various classification tasks.

Key words: Deep neural networks, Classification, Deep learning, Generative adversarial net


 
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How to Cite this Article
Pubmed Style

ALI BADIE, MOHAMMAD AMIN MORAGHEB, ALIREZA DEHGHAN, ALI NOSHAD. A COMPREHENSIVE ANALYSIS OF CLASSIFICATION MODELS BASED ON MACHINE AND DEEP LEARNING. JCR. 2021; 8(2): 1210-1219. doi:10.31838/jcr.08.02.124


Web Style

ALI BADIE, MOHAMMAD AMIN MORAGHEB, ALIREZA DEHGHAN, ALI NOSHAD. A COMPREHENSIVE ANALYSIS OF CLASSIFICATION MODELS BASED ON MACHINE AND DEEP LEARNING. http://www.jcreview.com/?mno=84202 [Access: May 28, 2021]. doi:10.31838/jcr.08.02.124


AMA (American Medical Association) Style

ALI BADIE, MOHAMMAD AMIN MORAGHEB, ALIREZA DEHGHAN, ALI NOSHAD. A COMPREHENSIVE ANALYSIS OF CLASSIFICATION MODELS BASED ON MACHINE AND DEEP LEARNING. JCR. 2021; 8(2): 1210-1219. doi:10.31838/jcr.08.02.124



Vancouver/ICMJE Style

ALI BADIE, MOHAMMAD AMIN MORAGHEB, ALIREZA DEHGHAN, ALI NOSHAD. A COMPREHENSIVE ANALYSIS OF CLASSIFICATION MODELS BASED ON MACHINE AND DEEP LEARNING. JCR. (2021), [cited May 28, 2021]; 8(2): 1210-1219. doi:10.31838/jcr.08.02.124



Harvard Style

ALI BADIE, MOHAMMAD AMIN MORAGHEB, ALIREZA DEHGHAN, ALI NOSHAD (2021) A COMPREHENSIVE ANALYSIS OF CLASSIFICATION MODELS BASED ON MACHINE AND DEEP LEARNING. JCR, 8 (2), 1210-1219. doi:10.31838/jcr.08.02.124



Turabian Style

ALI BADIE, MOHAMMAD AMIN MORAGHEB, ALIREZA DEHGHAN, ALI NOSHAD. 2021. A COMPREHENSIVE ANALYSIS OF CLASSIFICATION MODELS BASED ON MACHINE AND DEEP LEARNING. Journal of Critical Reviews, 8 (2), 1210-1219. doi:10.31838/jcr.08.02.124



Chicago Style

ALI BADIE, MOHAMMAD AMIN MORAGHEB, ALIREZA DEHGHAN, ALI NOSHAD. "A COMPREHENSIVE ANALYSIS OF CLASSIFICATION MODELS BASED ON MACHINE AND DEEP LEARNING." Journal of Critical Reviews 8 (2021), 1210-1219. doi:10.31838/jcr.08.02.124



MLA (The Modern Language Association) Style

ALI BADIE, MOHAMMAD AMIN MORAGHEB, ALIREZA DEHGHAN, ALI NOSHAD. "A COMPREHENSIVE ANALYSIS OF CLASSIFICATION MODELS BASED ON MACHINE AND DEEP LEARNING." Journal of Critical Reviews 8.2 (2021), 1210-1219. Print. doi:10.31838/jcr.08.02.124



APA (American Psychological Association) Style

ALI BADIE, MOHAMMAD AMIN MORAGHEB, ALIREZA DEHGHAN, ALI NOSHAD (2021) A COMPREHENSIVE ANALYSIS OF CLASSIFICATION MODELS BASED ON MACHINE AND DEEP LEARNING. Journal of Critical Reviews, 8 (2), 1210-1219. doi:10.31838/jcr.08.02.124