Surprisal-based algorithm for detecting anomalies in categorical data by Ossama Cherkaoui, Houda Anoun, Abderrahim Maizate

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Evaluation of the Performance of Unsupervised Learning Algorithms for Intrusion Detection in Unbalanced Data Environments by Gutierrez-Portela Fernando, Almenares Mendoza Florina, Calderon-Benavides Liliana

“…This study evaluated the performance of unsupervised machine learning algorithms for intrusion detection in unbalanced data environments using the BoT-IoT dataset. …”
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Data-driven network intrusion detection using optimized machine learning algorithms by Dauda Adeite Adenusi, Oladosu Oyebisi Oladimeji, Theopilus Adekunle Oyekola, Korede Solomon Olagunju

“…This study presents a comprehensive evaluation of machine learning approaches for network intrusion detection, comparing the performance of Decision Trees (DT), Random Forest (RF), K-Nearest Neighbors (K-NN), Gradient Boosting (GB), and Logistic Regression (LR) algorithms. …”
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Credit card fraud detection through machine learning algorithm by Agyan Panda, Bharath Yadlapalli, Zhi Zhou

“…Designing fraud detection algorithms is particularly difficult because to the non-stationary distribution of data, excessively skewed class distributions, and continuous streams of transactions. …”
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Improving lameness detection in cows: A machine learning algorithm application by Elma Dervić, Caspar Matzhold, Christa Egger-Danner, Franz Steininger, Peter Klimek

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Anomaly Detection Algorithms for Real-Time Log Data Analysis at Scale by Andras Horvath, Andras Olah, Attila Pinter, Balint Siklosi, Gergely Lukacs, Istvan Z. Reguly, Kalman Tornai, Tamas Zsedrovits, Zoltan Mathe

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Detection of Victimization Patterns and Risk of Gender Violence Through Machine Learning Algorithms by Edna Rocio Bernal-Monroy, Erika Dajanna Castañeda-Monroy, Rafael Ricardo Rentería-Ramos, Sixto Enrique Campaña-Bastidas, Jessica Barrera, Tania Maribel Palacios-Yampuezan, Olga Lucía González Gustin, Carlos Fernando Tobar-Torres, Zeneida Rocio Ceballos-Villada

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Learning Gaussian Bayesian Network from Censored Data Subject to Limit of Detection by the Structural EM Algorithm by Ping-Feng Xu, Shanyi Lin, Qian-Zhen Zheng, Man-Lai Tang

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Outlier Detection on High-Dimensional Data by wasan shaban, Murtadha Hamad

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A comparative assessment of machine learning models and algorithms for osteosarcoma cancer detection and classification by Amoakoh Gyasi-Agyei

“…Machine learning (ML) models trained on disease datasets are more effective in detection and classification than the conventional methods with hand-crafted features highly dependent on pathologists’ expertise. …”
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Exploring the State-of-the-Art Algorithms for Brain Tumor Classification Using MRI Data by Joice J Anish, D Ajitha

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Automatic detection of sleep spindles by neural networks algorithms by Jan Rychlík, Roman Mouček

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An Intrusion Detection Approach based on the Combination of Oversampling and Undersampling Algorithms by Ahmet Okan Arık, Gülsüm Çiğdem Çavdaroğlu

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Damage Detection and Identification on Elevator Systems Using Deep Learning Algorithms and Multibody Dynamics Models by Josef Koutsoupakis, Dimitrios Giagopoulos, Panagiotis Seventekidis, Georgios Karyofyllas, Amalia Giannakoula

“…For this purpose, a novel approach for damage detection and identification on elevator systems is developed in this work, where vibration data obtained through physical measurements and high-fidelity multibody dynamics models are combined with deep learning algorithms. …”
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A Framework for Network Intrusion Detection using Network Programmability and Data Stream Clustering Machine Learning Algorithms by Admilson de Ribamar Lima Ribeiro, Edward David Moreno Ordonez, Anderson Clayton Alves Nascimento

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Diagnosis and Detection of Alzheimer’s Disease Using Learning Algorithm by Gargi Pant Shukla, Santosh Kumar, Saroj Kumar Pandey, Rohit Agarwal, Neeraj Varshney, Ankit Kumar

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Automatic detection and classification of drill bit damage using deep learning and computer vision algorithms by Xiongwen Yang, Xiao Feng, Chris Cheng, Jiaqing Yu, Qing Zhang, Zilong Gao, Yang Liu, Bo Chen

“…Leveraging advancements in computer vision and deep learning algorithms, this research proposes an automated detection and classification method for polycrystalline diamond compact (PDC) bit damage. …”
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Detection of Irrigated and Non-Irrigated Soybeans Using Hyperspectral Data in Machine-Learning Models by Izabela Cristina de Oliveira, Ricardo Gava, Dthenifer Cordeiro Santana, Ana Carina da Silva Cândido Seron, Larissa Pereira Ribeiro Teodoro, Mayara Favero Cotrim, Regimar Garcia dos Santos, Rita de Cássia Félix Alvarez, Carlos Antonio da Silva Junior, Fábio Henrique Rojo Baio, Paulo Eduardo Teodoro

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Comparative Analysis of Machine Learning Models for Android Malware Detection by Adem Korkmaz, Selma Bulut

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Detecting Malicious URLs Using Classification Algorithms in Machine Learning and Deep Learning by Sira Astour, Ahmad Hasan

“…This study presents an improvement in the accuracy and speed of detecting malicious URLs through ensemble learning techniques, specifically Bagging (Bootstrap) and Stacking. …”
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