<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Most typical data mining techniques are developed based on training the batch data which makes the task of mining the data stream represent a significant challenge. On the other hand, providing a mechanism to perform data mining operations without revealing the patient’s identity has increasing importance in the data mining field. In this work, a classification model with differential privacy is proposed for mining the medical data stream using Adaptive Random Forest (ARF). The experimental results of applying the proposed model on four medical datasets show that ARF mostly has a more stable performance over the other six techniques.</p>
</abstract>

Most typical data mining techniques are developed based on training the batch data which makes the task of mining the data stream represent a significant challenge. On the other hand, providing a mechanism to perform data mining operations without revealing the patient’s identity has increasing importance in the data mining field. In this work, a classification model with differential privacy is proposed for mining the medical data stream using Adaptive Random Forest (ARF). The experimental results of applying the proposed model on four medical datasets show that ARF mostly has a more stable performance over the other six techniques.

Differential privacy based classification model for mining medical data stream using adaptive random forest

Acta Universitatis Sapientiae, Informatica

This work is licensed under the Creative Commons Attribution 4.0 International License.

Most typical data mining techniques are developed based on training the batch data which makes the task of mining the data stream represent a significant...

Differential privacy based classification model for mining medical data stream using adaptive random forest

Online veröffentlicht: 08. Juli 2021

Seitenbereich: 1 - 20

Eingereicht: 23. Jan. 2021

Akzeptiert: 28. Feb. 2021

DOI: https://doi.org/10.2478/ausi-2021-0001

Schlüsselwörter
ensemble methods, bagging, privacy-preserving protocol

© 2021 Hayder K. Fatlawi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Differential privacy based classification model for mining medical data stream using adaptive random forest

Online veröffentlicht: 08. Juli 2021

Seitenbereich: 1 - 20

Eingereicht: 23. Jan. 2021

Akzeptiert: 28. Feb. 2021

DOI: https://doi.org/10.2478/ausi-2021-0001

Schlüsselwörterensemble methods, bagging, privacy-preserving protocol

© 2021 Hayder K. Fatlawi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
ensemble methods, bagging, privacy-preserving protocol