Search Results - (( parameter optimization _ algorithm ) OR ( binary classification using algorithm ))

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

“…The features of the wood knot images are extracted using Gray Level Co-Occurrence Matrix. Binary Magnetic Optimization Algorithm is use to optimize the feature selection process. …”
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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. …”
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Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

“…Optimization algorithms are widely used for the identification of intrusion. …”
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Analysis Of Personal Protective Equipment Classification Method Using Deep Learning by Siti Zahrah Nur Ain, Silopung

“…Based on the result, CNN algorithm is a good algorithm as the binary classification of PPE achieved high accuracy result.…”
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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. …”
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An enhanced soft set data reduction using decision partition order technique by Mohammed, Mohammed Adam Taheir

“…Also, the accuracy of original soft-set optimal and sub-optimal results have been improved using an intelligent SSR-BPSO-BBO algorithm. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…Also, self-adaptive scaling factor and crossover probability control parameters are introduced to diminish time of finding an optimal parameter to produce the best population. …”
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Enhancement of new smooth support vector machines for classification problems by Santi Wulan, Purnami

“…To obtain optimal accuracy results, Uniform Design method is used to select parameter. …”
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Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

“…Three major factors that determine the performance of a machine learning are the choice of a representative set of features, choosing a suitable machine learning algorithm and the right selection of the training parameters for a specified machine learning algorithm. …”
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Task-state EEG signal classification for spatial cognitive evaluation based on multiscale high-density convolutional neural network by Wen, Dong, Li, Rou, Tang, Hao, Liu, Yijun, Wan, Xianglong, Dong, Xianling, Saripan, M. Iqbal, Lan, Xifa, Song, Haiqing, Zhou, Yanhong

“…Secondly, to enhance feature propagation and reduce the number of parameters, the dense network was connected after the multi-scale convolutional network, and the learning rate change function of the stochastic gradient descent algorithm was optimized to objectively evaluate the training effect. …”
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Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier by Siow, Shien Loong

“…There are a lot of feature extraction methods and classification methods for iris classification. Classic local binary pattern (LBP) is one of the most useful feature extraction methods. …”
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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

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Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data by Oyebayo, Olaniran Ridwan

“…These weights are in turn used to develop new impurity functions for selecting optimal splits for each tree in a forest. …”
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A New Quadratic Binary Harris Hawk Optimization For Feature Selection by Abdullah, Abdul Rahim, Too, Jing Wei, Mohd Saad, Norhashimah

“…A comparative study is conducted to compare the effectiveness of QBHHO with other feature selection algorithms such as binary differential evolution (BDE), genetic algorithm (GA), binary multi-verse optimizer (BMVO), binary flower pollination algorithm (BFPA), and binary salp swarm algorithm (BSSA). …”
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Development of compound clustering techniques using hybrid soft-computing algorithms by Salim, Naomie, Shamsuddin, Siti Mariyam, Salleh @ Sallehuddin, Roselina, Alwee, Razana

“…Initially, the heuristics needs user intervention to select optimal values, which give poor results. To overcome this problem, fuzzy memberships have been employed to find optimal parameters. …”
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EMG Feature Selection And Classification Using A Pbest-Guide Binary Particle Swarm Optimization by Too, Jing Wei, Tee, Wei Hown, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah

“…In order to measure the effectiveness of PBPSO, binary particle swarm optimization (BPSO), genetic algorithm (GA), modified binary tree growth algorithm (MBTGA), and binary differential evolution (BDE) were used for performance comparison. …”
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An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani by Ab Ghani, Nur Laila

“…The urban growth images obtained are analysed to improve existing classification algorithms. The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. …”
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Optimisation of support vector machine hyperparameters using enhanced artificial bee colony variant to diagnose breast cancer by Ravindran, Nadarajan

“…Machine learning offers a solution to these challenges, with support vector machines (SVM) being a popular choice for breast cancer diagnosis given its strength in binary classification, which suited well with the dataset used in this thesis. …”
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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.…”
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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. …”
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