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An analysis of intrusion detection classification using supervised machine learning algorithms on NSL-KDD dataset / Sarthak Rastogi ... [et al.]
Published 2022“…The IDS with machine learning method improves the detection accuracy of the security attacks. …”
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Comparison on machine learning algorithm to fast detection of malicious web pages
Published 2021“…Furthermore, previous approached have used blacklist technique which a conventional method and have shown promising result in detecting malicious webpages. …”
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Conference or Workshop Item -
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Improved intrusion detection algorithm based on TLBO and GA algorithms
Published 2021“…Optimization algorithms are widely used for the identification of intrusion. …”
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Autism Spectrum Disorder Classification Using Deep Learning
Published 2021“…Recently, deep learning methods have significantly sharpened the cutting edge of learning algorithms in a wide range of artificial intelligence tasks. …”
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Rao-SVM machine learning algorithm for intrusion detection system
Published 2020“…Most of the intrusion detection systems are developed based on optimization algorithms as a result of the increase in audit data features; optimization algorithms are also considered for IDS due to the decline in the performance of the human-based methods in terms of their training time and classification accuracy. …”
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Alternate methods for anomaly detection in high-energy physics via semi-supervised learning
Published 2020“…In this paper, we introduce two new algorithms called EHRA and C-EHRA, which use machine learning regression and clustering to detect anomalies in samples. …”
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Deep learning methods for facial expression recognition
Published 2019“…In this paper, we analyze various deep learning methods and their results. We have chosen Deep convolutional neural network as the best algorithms for facial expression detection and classification. …”
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Proceeding Paper -
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An ensemble deep learning classifier stacked with fuzzy ARTMAP for malware detection
Published 2023“…In addition, DL-based malware detection methods often entail single classifiers. …”
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A COLLABORATIVE FRAMEWORK FOR ANDROID MALWARE IDENTIFICATION USING DYNAMIC ANALYSIS
Published 2019“…The scope of this project focuses on Android Malware detection by using dynamic analysis. The methods to implement this project is through data collection, feature extraction, feature selection, and classification process. …”
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Final Year Project Report / IMRAD -
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The importance of data classification using machine learning methods in microarray data
Published 2021“…These emerging techniques can be used in detecting cancer. The swarm intelligence technique can be combined with other statistical methods for attaining better results.…”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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Development of Scoliotic spine severity detection using deep learning Algorithms
Published 2022“…Using Convolutional Neural Network (CNN), this research will integrate an artificial intelligence-assisted method for detecting and classifying Scoliosis illness types. …”
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Proceeding Paper -
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Ensemble based categorization and adaptive model for malware detection
Published 2011“…Current malware detection method involved string search algorithm which based on the pattern detection. …”
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Efficient feature selection analysis for accuracy malware classification
Published 2021“…This paper proposes a novel framework for Android malware detection. Our framework used three major methods for effective feature representation on malware detection and used this method to classify malware and benign. …”
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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool
Published 2018“…From the data analysis using WEKA software, the production rules classifier (PART) is found to be the most accurate classification algorithm in classifying the emotion which yields the highest precision percentage of 99.6% compared to J48 (99.5%) and Naïve Bayes (96.2%). …”
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A new model for iris data set classification based on linear support vector machine parameter's optimization
Published 2020“…In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.…”
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Breast Cancer Detection Using Image Processing and Machine Learning
Published 2024“…Using the K-Nearest Neighbors (KNN) algorithm is one such technique. …”
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