Search Results - (( variable learning based algorithm ) OR ( effective classification using algorithm ))

Gas Identi cation by Using a Cluster-k-Nearest-Neighbor by Brahim Belhaouari, samir

“…We find 98.7% of accuracy in the classification of 6 different types of Gas by using K-means cluster algorithm and we find almost the same by using the new clustering algorithm.…”
Get full text
Get full text

Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

“…Therefore, this research has designed fuzzy learning algorithm that is able to classify fruits based on their shape and size features using Harumanis dataset. …”
Get full text
Get full text

A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification by Talpur, N., Abdulkadir, S.J., Hasan, M.H., Alhussian, H., Alwadain, A.

“…The performance of the proposed SCSO algorithm was compared with six state-of-the-art and recent wrapper-based optimization algorithms using the validation metrics of classification accuracy, optimum feature size, and computational cost in seconds. …”
Get full text
Get full text

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

Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.] by Mohd, Thuraiya, Jamil, Syafiqah, Masrom, Suraya, Ab Rahim, Norbaya

“…This experiment used five common machine learning algorithms namely 1) Linear Regressor, 2) Decision Tree Regressor, 3) Random Forest Regressor, 4) Ridge Regressor and 5) Lasso Regressor tested on a real estate data-set of covering Kuala Lumpur District, Malaysia. 3 set of experiments was conducted based on the different feature selections and purposes The results show that the implementation of 16 variables based on Experiment 2 has given a promising effect on the model compare the other experiment, and the Random Forest Regressor by using the Split approach for training and validating data-set outperformed other algorithms compared to Cross-Validation approach. …”
Get full text
Get full text

Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

“…The optimal combination of λ and training sequence can be computed efficiently using a genetic permutation algorithm. The best combinations were selected to train individual ARTMAPs as voting members, and the final class predictions were determined using probabilistic ensemble voting strategy. …”
Get full text
Get full text

A machine learning approach of predicting high potential archers by means of physical fitness indicators by Musa, Rabiu Muazu, Anwar, P. P. Abdul Majeed, Zahari, Taha

“…k-nearest neighbour (k-NN) has been shown to be an effective learning algorithm for classification and prediction. …”
Get full text
Get full text
Get full text

Improving hand written digit recognition using hybrid feature selection algorithm by Wong, Khye Mun

“…While mRMR was capable of identifying a subset of features that were highly relevant to the targeted classification variable, it still carry the weakness of capturing redundant features along with the algorithm. …”
Get full text
Get full text

A machine learning approach of predicting high potential archers by means of physical fitness indicators by Muazu Musa, Rabiu, Abdul Majeed, Anwar P.P., Taha, Zahari, Chang, Siow Wee, Ab. Nasir, Ahmad Fakhri, Abdullah, Mohamad Razali

“…k-nearest neighbour (k-NN) has been shown to be an effective learning algorithm for classification and prediction. …”
Get full text
Get full text

The Identification of High Potential Archers Based on Fitness and Motor Ability Variables: A Support Vector Machine Approach by Zahari, Taha, Rabiu Muazu, Musa, Anwar, P. P. Abdul Majeed, Muhammad Muaz, Alim, Mohamad Razali, Abdullah

“…Support Vector Machine (SVM) has been shown to be an effective learning algorithm for classification and prediction. …”
Get full text
Get full text
Get full text

Predicting Cheaters in PlayerUnknown’s Battlegrounds (PUBG) using Random Forest Algorithm by Nurin Alya, Haris

“…The primary goal is to use the Random Forest algorithm, an effective machine learning technique, to predict instances of cheating based on the behavioural patterns of participants. …”
Get full text
Get full text
Get full text

SpickME: Choosing spectacles prediction system by using multinomial Naïve Bayes / Nurul Nabilah Johari by Johari, Nurul Nabilah

Get full text
Get full text

A Stacked Ensemble Deep Learning Approach For Imbalanced Multi-class Water Quality Index Prediction by Wen Yee Wong, Khairunnisa Hasikin, Anis Salwa Mohd Khairuddin, Sarah Abdul Razak, Hanee Farzana Hizaddin, Mohd Istajib Mokhtar, Muhammad Mokhzaini Azizan

An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

“…Additionally, the research restricts the number of variables through feature selection to enhance the performance of the algorithm. …”
Get full text
Get full text

Tree species and aboveground biomass estimation using machine learning, hyperspectral and LiDAR data / Nik Ahmad Faris Nik Effendi by Nik Effendi, Nik Ahmad Faris

“…Besides, Artificial Neural Network (ANN) and Random Forest (RF) algorithm was used to predicted the AGB using different combination of variables. …”
Get full text
Get full text

Diagnostic power of resting-state fMRI for detection of network connectivity in Alzheimer's disease and mild cognitive impairment: a systematic review by Ibrahim, Buhari, Suppiah, Subapriya, Ibrahim, Normala, Mohamad, Mazlyfarina, Abu Hassan, Hasyma, Syed Nasser, Nisha, Saripan, M. Iqbal

“…Nevertheless, various concerns over the homogeneity of data based on patient selection, scanner effects, and the variable usage of classifiers and algorithms pose a challenge for ML-based image interpretation of rs-fMRI datasets to become a mainstream option for diagnosing AD and predicting the conversion of HC/MCI to AD.…”
Get full text
Get full text
Get full text

A robust prioritization framework of data quality dimensions to improve ML-driven healthcare systems using AHP and sensitivity analysis by Al-Hgaish, Areen Metib, Atan, Rodziah, Yaakob, Razali, Osman, Mohd Hafeez

“…The success of Machine Learning (ML) models in healthcare relies heavily on the quality of data used. …”
Get full text
Get full text
Get full text

Risk perception modeling based on physiological and emotional responses / Ding Huizhe by Ding , Huizhe

“…It was demonstrated that the primary results derived from statistical analysis and machine learning modelling were remarkably consistent, thereby confirming the effectiveness and generalization of the proposed weight adjustment algorithm, particularly in situations with closely matched risk levels. …”
Get full text
Get full text
Get full text

Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease by Che Hashim, Izrahayu

“…As the ALOS PALSAR-2 image was evaluated with dual-polarization (HH and HV), each digitized point has two distinct backscatter data with four severity levels (T0 to T3). The machine learning algorithm consistently performs well when presented with a well-balanced dataset. …”
Get full text
Get full text

A comparative study on aviation arrival delay prediction using machine learning methods by Chew, Pui Ting

“…Hence, the best performing method in this research can be used to predict flight arrival delays to reduce the above-mentioned flight delay costs and aid the classification of high or low risks of the insured to be used as input for future work to calculate insurance premium based on the sum of mean and standard deviation of losses.…”
Get full text