Predictive Model of Psychoactive Drugs Consumption using Classification Machine Learning Algorithms by Almahmood, Mothanna

“…Eighteen classification models were built using different classification algorithms such as Gaussian Naive Bais, Logistic Regression, k-nearest neighbors, Random Forest, and Decision Tree. …”
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An Optimized Feature Selection Technique in Diversified Natural Scene Text for Classification Using Genetic Algorithm by Ghulam Jillani Ansari (16896342)

“…The Support Vector Machine (SVM) algorithm is used for classification and the average F-Score is used as fitness function and target condition. …”

Optimizing Document Classification: Unleashing the Power of Genetic Algorithms by Ghulam Mustafa (458105)

“…Additionally, our proposed model optimizes the features using a genetic algorithm. Optimal feature selection performances a crucial role in this domain, enhancing the overall accuracy of the document classification system while reducing the time complexity associated with selecting the most relevant features from this large-dimensional space. …”

Arabic Text Classification Using Modified Artificial Bee Colony Algorithm for Sentiment Analysis: The Case of Jordanian Dialect by Habeeb, Abdallah

“…The second phase, modified the Artificial Bee Colony (ABC) Algorithm, with Upper Confidence Bound (UCB) Algorithm, to promote the exploitation ability for the minimum dimension, to get the minimum number of the optimal feature, then using forward feature selection strategy by four classifiers of machine learning algorithms: (K-Nearest Neighbors (KNN), Support vector machines (SVM), Naïve-Bayes (NB), and Polynomial Neural Networks (PNN). …”
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Performance Prediction Using Classification by MOOLIYIL, GITA

“…The use of classification as a data mining approach for performance prediction has been studied by many eminent researchers. …”
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A Study on Applying Data Mining in Airline Industry for Demand Forecasting by predicting Item Criticality by KARAM, ZAINAB HAMDAN

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Exploring Semi-Supervised Learning Algorithms for Camera Trap Images by Sajun, Ali Reza

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LDSVM: Leukemia Cancer Classification Using Machine Learning by Abdul Karim (417009)

Intelligent Fusion of Deep Features for Improved Waste Classification by Kashif Ahmad (12592762)

Fault detection and classification in hybrid energy-based multi-area grid-connected microgrid clusters using discrete wavelet transform with deep neural networks by S. N. V. Bramareswara Rao (21768302)

“…The proposed DWT-DNN first extracts the input features from the point of common coupling of the cluster system using DWT, and then, these decomposed features are applied as input variables to train the DNN for the detection and classification of various faults. …”

An efficient approach for textual data classification using deep learning by Abdullah Alqahtani (7128143)

“…<p dir="ltr">Text categorization is an effective activity that can be accomplished using a variety of classification algorithms. In machine learning, the classifier is built by learning the features of categories from a set of preset training data. …”

FPGA-Based Network Traffic Classification Using Machine Learning by Elnawawy, Mohammed

“…The proposed design achieves an average throughput of 163.24 Gbps, exceeding throughputs of reported hardware-based classifiers that use comparable approaches, which in turn ensures the continuity of realtime traffic classification at congested data centers.…”
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FPGA-Based Network Traffic Classification Using Machine Learning by Elnawawy, Mohammed

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Lung cancer medical images classification using hybrid CNN-SVM by Abdulrazak Yahya Saleh (18520026)

“…This paper presents an image classification method based on the hybrid Convolutional Neural Network (CNN) algorithm and Support Vector Machine (SVM). …”

Unsupervised Deep Learning for Classification Of Bats Calls Using Acoustic Data by Arshad, Muhammad Arbab

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Machine learning approach for the classification of corn seed using hybrid features by Aqib Ali (19680145)

“…The nine optimized features have been acquired by employing the correlation-based feature selection (CFS) technique with the Best First search algorithm. To build the classification models, Random forest (RF), BayesNet (BN), LogitBoost (LB), and Multilayer Perceptron (MLP) were employed using optimized multi-feature using (10-fold) cross-validation approach. …”

The Detection of Dysarthria Severity Levels Using AI Models: A Review by Afnan Al-Ali (16888695)

TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection by Zina Chkirbene (16869987)

“…The final classification decision for both models is estimated by incorporating the node's past behavior with the machine learning algorithm. …”

On the performance of fusion based planet-scope and Sentinel-2 data for crop classification using inception inspired deep convolutional neural network by Nasru Minallah (9427338)

AN ALGORITHM FOR IRIS IDENTIFICATION USING FOURIER DESCRIPTORS by Deriche, M.

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