Machine Learning Algorithms with Different Gene Expression Datasets
M Ramachandro1, Ravi Bhramaramba2
1M Ramachandro, Department of Computer Science & Engineering, GMR Institute of Technology, (Andhra Pradesh), India.
2Ravi Bhramaramba, Department of Computer Science & Engineering, GITAM, Visakhapatnam (Andhra Pradesh), India.
Manuscript received on 23 November 2019 | Revised Manuscript received on 11 December 2019 | Manuscript Published on 30 December 2019 | PP: 186-190 | Volume-9 Issue-2S3 December 2019 | Retrieval Number: B10471292S319/2019©BEIESP | DOI: 10.35940/ijitee.B1047.1292S319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Two classification techniques have been compared using microarray dataset. For example SVM, Logistic Regression strategies have been utilized in the process. The usefulness of these techniques has been determined with precision, accuracy, recall and F1-Scores. These techniques Here Prostate tumors, Lung Cancer, were analyzed. For each situation these strategies were applied to two distinctive microarray datasets with two classes. Finally performance analysis was done.
Keywords: About four Key Words or Phrases in Alphabetical Order, Separated by Commas.
Scope of the Article: Machine Learning