Search Results - (( feature selection method algorithm ) OR ( data visualization using algorithm ))

Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms by Rachmad, Iqbal, Tri Basuki, Kurniawan, Misinem, ., Edi Surya, Negara, Tata, Sutabri

“…The classification algorithm used in this research is the Convolutional Neural Network (CNN) algorithm. …”
Get full text
Get full text
Get full text
Get full text

Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network by Zafar, R., Kamel, N., Naufal, M., Malik, A.S., Dass, S.C., Ahmad, R.F., Abdullah, J.M., Reza, F.

“…Selection of significant features is an important part of fMRI data analysis, since it reduces the computational burden and improves the prediction performance; significant features are selected using t -test. …”
Get full text
Get full text

Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization by Nanyonga Aziida, Sorayya Malek, Firdaus Aziz, Khairul Shafiq Ibrahim, Sazzli Kasim

“…Identifying a feature selection method with a classifier algorithm that produces high performance in mortality studies is essential and has not been reported before. …”
Get full text
Get full text
Get full text

Transient analysis for leak signature identification based on Hilbert Huang transform and integrated kurtosis algorithm for z-notch filter technique by Muhammad Hanafi, Yusop

“…However, this method has the difficulty in selecting the suitable IMF for the next data post-processing method, which is Hilbert Transform (HT). …”
Get full text
Get full text

Spectral texture segmentation of Magnetic Resonance Imaging (MRI) brain images for glioma brain tumour detection / Rosniza Roslan by Roslan, Rosniza

“…Experiments conducted on 64 MRI images, of all sequences showed that texture energy is the best texture feature to be used in glioma segmentation. Fuzzy C-Means clustering algorithm is then used to segment texture energy features from 126 MRI brain images of all sequences. …”
Get full text
Get full text

P300 detection of brain signals using a combination of wavelet transform techniques by Motlagh, Farid Esmaeili

“…This research is proving the power of combination of discrete and continuous wavelet transform for achieving high accuracy in single trial detection and visualization of P300. Meanwhile the new approaches in channels selection methods help the algorithms for convenient online usage.…”
Get full text
Get full text

Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh by Sai , Chong Yeh

“…The training and parameters selection of the machine learning algorithms are conducted using EEG data collected from ten subjects in the laboratory. …”
Get full text
Get full text
Get full text

A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

“…It has been found that PCA, DOBIN, Stray algorithm, and DAE-KNN have a high learning rate compared to Random projection, ROBEM, and OCP methods. …”
Get full text
Get full text

A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

“…It has been found that PCA, DOBIN, Stray algorithm, and DAE-KNN have a high learning rate compared to Random projection, ROBEM, and OCP methods. …”
Get full text
Get full text

A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

“…It has been found that PCA, DOBIN, Stray algorithm, and DAE-KNN have a high learning rate compared to Random projection, ROBEM, and OCP methods. …”
Get full text
Get full text

A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

“…It has been found that PCA, DOBIN, Stray algorithm, and DAE-KNN have a high learning rate compared to Random projection, ROBEM, and OCP methods. …”
Get full text
Get full text

A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

“…It has been found that PCA, DOBIN, Stray algorithm, and DAE-KNN have a high learning rate compared to Random projection, ROBEM, and OCP methods. …”
Get full text
Get full text

A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Akmar Ismail, Saidatul, Mahdin, Hairulnizam

“…It has been found that PCA, DOBIN, Stray algorithm, and DAE-KNN have a high learning rate compared to Random projection, ROBEM, and OCP methods. …”
Get full text
Get full text

A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Akmar Ismail, Saidatul, Mahdin, Hairulnizam

“…It has been found that PCA, DOBIN, Stray algorithm, and DAE-KNN have a high learning rate compared to Random projection, ROBEM, and OCP methods. …”
Get full text
Get full text

Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining by Ang, Yuhao, Mohd Shafri, Helmi Zulhaidi, Al-Habshi, Mohammed Mustafa

“…Materials and Methods: We used hyperspectral reflectance data from healthy and FLS of soybeans. …”
Get full text
Get full text
Get full text

EEG-Based Person Authentication Modelling Using Incremental Fuzzy-Rough Nearest Neighbour Technique by Liew, Siaw Hong

“…The correlation-based feature selection (CFS) method was used to select representative WPD vector subset to eliminate redundancy before combining with other features. …”
Get full text
Get full text
Get full text
Get full text

Deep Reinforcement Learning For Control by Bakar, Nurul Asyikin Abu

“…In essence, the method is to use a reward-based learning environment to watch how the agent makes decisions. …”
Get full text
Get full text

Sustainable urban drainage systems (2014-2023) by using bibliometric analysis method / Abraham Ayuen Ngong Deng, Nursetiawan and Jazaul Ikhsan by Ngong Deng, Abraham Ayuen, -, Nursetiawan, Ikhsan, Jazaul

“…Developing bibliometric methods and adding feature extraction algorithms when selecting features used to model data can increase the efficiency and accuracy of the data on sustainable urban drainage systems. …”
Get full text
Get full text

Oil palm female inflorescences anthesis stages identification using selected emissivities through thermal imaging and Machine Learning by Yousefidashliboroun, Mamehgol

“…However, the ensemble method on emissivity of 0.98 using endogenous and endogenous+exogenous feature sets resulted in F-measure score of 57.81% and 86.63%, respectively lower than that of the latter. …”
Get full text
Get full text
Get full text

High-Resolution Downscaling with Interpretable Relevant Vector Machine: Rainfall Prediction for Case Study in Selangor by Abdul Rashid, Raghdah Rasyidah, Shaharudin, Shazlyn Milleana, Sulaiman, Nurul Ainina Filza, Zainuddin, Nurul Hila, Mahdin, Hairulnizam, Mohd Najib, Summayah Aimi, Hidayat, Rahmat

“…While machine learning eliminates the requirement for manual feature selection when extracting significant information from predictor fields, considering multiple pivotal factors is essential. …”
Get full text
Get full text