1.

An Efficient Feature Engineering Method for Fraud Detection in E-commerce

Volume 21, Issue 3, September 2021, Pages 40-52
Suha M. Najem; Suhad kadhem
2.

Anomaly Detection by Using Hybrid Method

Volume 9, Issue 1, June 2017, Pages 99-107
Mohamed H. Ghaleb
3.

Comparing SVR and Random Forest Forecasting based on Autoregressive Time Series with Application

Volume 20, Issue 2, December 2023, Pages 155-165
Naam Salem Fadhil; Zinah Mudher ALbazzaz
4.

Detection of Obesity Stages Using Machine Learning Algorithms

Volume 14, Issue 1, May 2023, Pages 80-88
Sukru Kitis; Hanife Goker
5.

Finding Accurate And Comprehensible Knowledge Discovery In Database Model

Volume 21, Issue 3, April 2013, Pages 725-745
Abbas M. AL-Bakry
6.

Handling missing Data values in a Database Model using Random Forest

Volume 20, Issue 2, June 2012, Pages 482-486
Abbas M. AL-Bakry
7.

Machine Learning for Identifying Fraud in Credit Card Transactions

Volume 24, Issue 1, March 2024, Pages 71-83
Mohammad Abd Abbas; Bilal Ghazal Ghazal; Ahmad ghandour Ghandour
8.

Meerkat Clan-Based Feature Selection in Random Forest Algorithm for IoT Intrusion Detection

Volume 22, Issue 3, September 2022, Pages 15-24
Adil Yousef Hussein; Ahmed T. Sadiq
9.

Predicting Incident Duration Based on Machine Learning Methods

Volume 21, Issue 1, March 2021, Pages 1-15
Zainab Ali Mohammed; Mohammed Najm Abdullah2; Imad Husain Al Hussaini
10.

Random Forest (RF) and Artificial Neural Network (ANN) Algorithms for LULC Mapping

Volume 38, 4A, April 2020, Pages 510-514
Tay H. Shihab; Amjed N. Al-Hameedawi; Ammar M. Hamza
11.

Textual Dataset Classification Using Supervised Machine Learning Techniques

Volume 40, Issue 4, April 2022, Pages 527-538
Hanan Q. Jaleel; Jane J. Stephan; Sinan A. Naji
12.

Using intelligence techniques to automate Oracle testing

Volume 17, Issue 1, June 2023, Pages 91-97
Nour Sulaiman; safwan hasson


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