Search Results - (( binary classification system algorithm ) OR ( data classification problem algorithm ))

An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…Major problems in classification task are large amount of training data, large number of features and different behavior of data streams that reduce accuracy and increase computational cost in classifier training phase. …”
Get full text
Get full text

Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

“…In this regard, this thesis proposes five FS methods for efficient EMG signals classification. The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
Get full text
Get full text
Get full text

Hybrid ensemble learning techniques for intrusion detection systems in Internet of Things security by Soni

“…The first technique employed the XGBoost and LightGBM algorithms to solve a binary classification problem across seven different datasets. …”
Get full text
Get full text

Rao-SVM machine learning algorithm for intrusion detection system by Abd, Shamis N., Alsajri, Mohammad, Ibraheem, Hind Raad

“…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. …”
Get full text
Get full text
Get full text

Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

“…This is attributable to the increasing number of audit data features and the decreasing performance of human-based smart Intrusion Detection Systems (IDS) regarding classification accuracy and training time. …”
Get full text
Get full text
Get full text

Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

“…Based on the above components and circumstances, many studies have been performed on data clustering problems. Despite attempts to solve the data clustering issues, there are also many variants of modified algorithms in traditional information clustering that attempt to solve issues such as clustering algorithms based on condensation. …”
Get full text
Get full text

New Algorithm of Location Model based on Robust Estimators and Smoothing Approach by Hamid, Hashibah

Get full text
Get full text
Get full text

Global and local clustering soft assignment for intrusion detection system: a comparative study by Mohd Rizal Kadis, Azizi Abdullah

“…The ability of IDS to detect new sophisticated attacks compared to traditional method such as firewall is important to secure the network. Machine Learning algorithm such as unsupervised learning and supervised learning is capable to solve the problem of classification in IDS. …”
Get full text
Get full text
Get full text

A survey on improvement of Mahalanobis Taguchi system and its application by Tan L.M., Wan Muhamad W.Z.A., Yahya Z.R., Junoh A.K., Azziz N.H.A., Ramlie F., Harudin N., Abu M.Y., Tan X.J.

Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…In order to improve recognition of high interclass similarity activities, One-Versus- All (OVA) binarization strategy is introduced by transforming original multi-class classification problems into a series of two-class classification problems. …”
Get full text
Get full text

Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout by Dzakiyullah, Nur Rachman

“…The first experiment revealed that the Algorithm Adaptation framework outperformed Problem Transformation methods across most metrics. …”
Get full text
Get full text

Named entity recognition using a new fuzzy support vector machine. by Mansouri, Alireza, Affendy, Lilly Suriani, Mamat, Ali

“…In our method we have employed Support Vector Machine as one of the best machine learning algorithm for classification and we contribute a new fuzzy membership function thus removing the Support Vector Machine’s weakness points in NER precision and multi classification. …”
Get full text
Get full text

Common spatial pattern with feature scaling (FSc-CSP) for motor imagery classification by Prathama, Y.B.H., Shapiai, M.I., Aris, S.A.M., Ibrahim, Z., Jaafar, J., Fauzi, H.

Get full text
Get full text

Enhanced Adaptive Neuro-Fuzzy Inference System Classification Method for Intrusion Detection by Jia, Liu

“…However, due to the inherent uncertainty in distinguishing between normal and abnormal behaviours, intrusion detection problems can be considered as fuzzy classification problems. …”
Get full text
Get full text
Get full text
Get full text

Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier by Siow, Shien Loong

“…Due to the current methods in feature extraction are still improving, this project proposed a new feature extraction method to increase the performance of iris classification. In this project, a classification system is proposed with the one-dimensional local binary pattern algorithm (1D-LBP) with the K-Nearest Neighbour (K-NN) classifier and the system is developed by using a Raspberry Pi 3.There are eight different subjects used to classify in this classification system and each subject consists of seven samples of normalized iris image as input to the system. …”
Get full text
Get full text

Performances of machine learning algorithms for binary classification of network anomaly detection system by Nawir, M., Amir, A., Lynn, O.B., Yaakob, N., Ahmad, R.B.

“…The finding showed that AODE algorithm is performed well in term of accuracy and processing time for binary classification towards UNSW-NB15 dataset.…”
Get full text
Get full text
Get full text

Feature Selection using Binary Simulated Kalman Filter for Peak Classification of EEG Signals by Badaruddin, Muhammad, Mohd Falfazli, Mat Jusof, Mohd Ibrahim, Shapiai, Asrul, Adam, Zulkifli, Md. Yusof, Kamil Zakwan, Mohd Azmi, Nor Hidayati, Abdul Aziz, Zuwairie, Ibrahim, Norrima, Mokhtar

Get full text
Get full text

Classification System for Wood Recognition using K-Nearest Neighbor with Optimized Features from Binary Gravitational Algorithm by Taman, Ishak, Md Rosid, Nur Atika, Karis, Mohd Safirin, Hasim, Saipol Hadi, Zainal Abidin, Amar Faiz, Nordin, Nur Anis, Omar, Norhaizat, Jaafar, Hazriq Izzuan, Ab Ghani, Zailani, Hassan, Jefery

“…The project proposes a classification system using Gray Level Co-Occurrence Matrix (GLCM) as feature extractor, K-Nearest Neighbor (K-NN) as classifier and Binary Gravitational Search Algorithm (BGSA) as the optimizer for GLCM’s feature selection and parameters. …”
Get full text
Get full text

Improving amphetamine-type stimulants drug classification using chaotic-based time-varying binary whale optimization algorithm by Draman @ Muda, Azah Kamilah, Mohd Yusof, Norfadzlia, Pratama, Satrya Fajri, Carbo-Dorca, Ramon, Abraham, Ajith

Get full text
Get full text
Get full text

A Preliminary Study of Wood Species Classifacation System Based on Wood Knot Texture Using K-Nearest Neighbour With Optimized Features From Binary Magnetic Optimization Algorithm S... by Osman, Khairuddin, Mohamad, Syahrul Hisham, Jaafar, Hazriq Izzuan

Get full text
Get full text