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Fisher score and Matthews correlation coefficient-based feature subset selection for heart disease diagnosis using support vector machines.

, , , , , , and . Knowl. Inf. Syst., 58 (1): 139-167 (2019)

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Support Vector Machines-based Heart Disease Diagnosis using Feature Subset, Wrapping Selection and Extraction Methods., , , and . Comput. Electr. Eng., (2020)Using app reviews for competitive analysis: tool support., , and . WAMA@ESEC/SIGSOFT FSE, page 40-46. ACM, (2019)Simulating the Impact of Annotation Guidelines and Annotated Data on Extracting App Features from App Reviews., , and . ICSOFT, page 384-396. SciTePress, (2019)Video Summarization: Techniques and Classification., , , , and . ICCVG, volume 7594 of Lecture Notes in Computer Science, page 1-13. Springer, (2012)An efficient cryptographic technique using modified Diffie-Hellman in wireless sensor networks., , , , , , , and . Int. J. Distributed Sens. Networks, 16 (6): 155014772092577 (2020)Simplifying the Classification of App Reviews Using Only Lexical Features., , and . ICSOFT (Selected Papers), volume 1077 of Communications in Computer and Information Science, page 173-193. Springer, (2018)Fisher score and Matthews correlation coefficient-based feature subset selection for heart disease diagnosis using support vector machines., , , , , , and . Knowl. Inf. Syst., 58 (1): 139-167 (2019)Is the SAFE Approach Too Simple for App Feature Extraction? A Replication Study., , and . REFSQ, volume 11412 of Lecture Notes in Computer Science, page 21-36. Springer, (2019)