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Logistic Regression Method for Sarcasm Detection of Text Data
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 177 - Number 26 |
| Year of Publication: 2019 |
| Authors: Bipin Gupta, Ankur Gupta |
10.5120/ijca2019919451
|
Bipin Gupta, Ankur Gupta . Logistic Regression Method for Sarcasm Detection of Text Data. International Journal of Computer Applications. 177, 26 ( Dec 2019), 1-4. DOI=10.5120/ijca2019919451
Abstract
The prediction analysis is approach which can predict future possibilities. This research work is based on the sarcasm detection from the text data. In the previous time SVM classification is applied for the sarcasm detection. The SVM classifier classifies data based on the hyper plane which give low accuracy. To improve accuracy for sarcasm detection logistic regression is applied in this work. The existing and proposed techniques are implemented in python and results are analyzed in terms of accuracy, execution time. The proposed approach has high accuracy and low execution time as compared to SVM classifier for sarcasm detection
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