Search Results - (( parameter optimization method algorithm ) OR ( label classification techniques algorithm ))

Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

“…The advantage of the cluster labelling algorithm compared to co-spectral plot and maximum-likelihood classifier was the algorithm provided a rapid production of high accuracy classification map.…”
Get full text
Get full text

Nearest neighbour group-based classification by Samsudin, Noor A., Bradley, Andrew P.

“…In this paper, we extend three variants of the nearest neighbour algorithm to develop a number of non-parametric group-based classification techniques. …”
Get full text
Get full text
Get full text

An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

“…The primary objective is to determine the optimal technique for predicting relevant class labels. The paper emphasizes the significance of discretization in data preprocessing, offering a comprehensive approach that combines discretization techniques with optimization algorithms. …”
Get full text
Get full text
Get full text

An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

“…The primary objective is to determine the optimal technique for predicting relevant class labels. The paper emphasizes the significance of discretization in data preprocessing, offering a comprehensive approach that combines discretization techniques with optimization algorithms. …”
Get full text
Get full text
Get full text

Multi-label learning based on positive label correlations using predictive apriori by Al Azaidah, Raed Hasan Saleh

“…Multi-label Learning (MLL) is a general task in data mining that consists of three main tasks: classification, label ranking, and multi-label ranking. …”
Get full text
Get full text
Get full text
Get full text

Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

“…For this reason, in this research,several auxiliary algorithms are introduced to improve the performance of the classification algorithm, namely the meta-heuristic algorithm. …”
Get full text
Get full text
Get full text

Fuzzy classification based on combinative algorithms with fuzzy similarity measure / Nur Amira Mat Saffie by Mat Saffie, Nur Amira

“…The performance of a single-model (classifier) can be determined on the basis of the classification accuracy. However, it is difficult to determine which single-model is the best classification technique in a specific application domain since a single learning algorithm may not uniformly outperform other algorithms over various datasets. …”
Get full text
Get full text

Context enrichment framework for sentiment analysis in handling word ambiguity resolution by Yusof, Nor Nadiah

“…For classification performances, optimization of machine learning parameters and exploration of deep learning approaches can be applied for further enhancement.…”
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

“…Seven machine learning models—Artificial Neural Network (ANN), Random Forest (RF), Decision Tree (DTT), k-Nearest Neighbors (k-NN), Naïve Bayes (NB), Support Vector Machine (SVM), and Deep Neural Network (DNN)—were used for multi-label classification of the complications. The study employed two MLC frameworks: Problem Transformation methods (Binary Relevance, Classifier Chains, Label Power Set, and Calibrated Label Ranking) and Algorithm Adaptation. …”
Get full text
Get full text
Get full text

An enhanced feature selection technique for classification of group based holy Quran verses by Abdullahi Oyekunle, Adeleke

“…This thesis is about proposing an enhanced feature selection technique for text classification applications. Text classification problem is primarily applied in document labeling. …”
Get full text
Get full text
Get full text
Get full text

A comparative study in classification techniques for unsupervised record linkage model by Ektefa, Mohammadreza, Sidi, Fatimah, Ibrahim, Hamidah, A. Jabar, Marzanah, Memar, Sara

“…In order to utilize the supervised classification algorithms without consuming a lot of time for labeling data manually, a two step method which selects the training data automatically has been proposed in previous studies. …”
Get full text
Get full text
Get full text

Improvement anomaly intrusion detection using Fuzzy-ART based on K-means based on SNC Labeling by Zulaiha Ali Othman, Afaf Muftah Adabashi, Suhaila Zainudin, Saadat M. Al Hashmi

“…This paper presents our work to improve the performance of anomaly intrusion detection using Fuzzy-ART based on the K-means algorithm. The K-means is a modified version of the standard K-means by initializing the value K from the value obtained after data mining using Fuzzy-ART and SNC labeling technique. …”
Get full text
Get full text
Get full text

Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd by Nur Farahaina, Idris

“…The proposed technique solves the limitation of the classic ID3 algorithm that cannot classify the continuous-valued attributes and, at the same time, increase the classification accuracy. …”
Get full text
Get full text

An enhanced feature selection technique for classification of group-based holy quran verses by Oyekunle, Adeleke Abdullahi

“…This thesis is about proposing an enhanced feature selection technique for text classification applications. Text classification problem is primarily applied in document labeling. …”
Get full text
Get full text
Get full text
Get full text

Dynamic android malware category classification using semi-supervised deep learning by Mahdavifar, Samaneh, Kadir, Andi Fitriah Abdul, Fatemi, Rasool, Alhadidi, Dima, Ghorbani, Ali A

“…We evaluate our proposed model on CICMalDroid2020 and conduct a comparison with Label Propagation (LP), a well-known semi-supervised machine learning technique, and other common machine learning algorithms. …”
Get full text
Get full text
Get full text
Get full text
Get full text

VEHICLE CLASSIFICATION USING NEURAL NETWORKS AND IMAGE PROCESSING by ONG KANG WEI, ONG KANG WEI, LOH SER LEE, LOH SER LEE

“…The aim of this study is to propose a vehicle classification scheme where YOLO v5 algorithm and Faster R-CNN algorithm are being implemented separately into vehicle classification, followed by comparison of result between these two algorithms. …”
Get full text
Get full text
Get full text

An efficient algorithm for cardiac arrhythmia classification using ensemble of depthwise Separable convolutional neural networks by Ihsanto, Eko, Ramli, Kalamullah, Sudiana, Dodi, Gunawan, Teddy Surya

“…Many algorithms have been developed for automated electrocardiogram (ECG) classification. …”
Get full text
Get full text
Get full text
Get full text

Improving multi-resident activity recognition in smart home using multi label classification with adaptive profiling by Mohamed, Raihani

“…Furthermore, there is tendency that multi label classifications used instead of traditional single label classification technique. …”
Get full text
Get full text

An improved defect classification algorithm for six printing defects and its implementation on real printed circuit board images by Ibrahim, I., Ibrahim, Z., Khalil, K., Mokji, M.M., Abu Bakar, S.A.R.S., Mokhtar, N., Ahmad, W.K.W.

“…The defect classification algorithm is improved by incorporating proper image registration and thresholding techniques to solve the alignment and uneven illumination problem. …”
Get full text
Get full text
Get full text

Improved relative discriminative criterion using rare and informative terms and ringed seal search-support vector machine techniques for text classification by Sharif, Wareesa

“…These techniques are expected particularly to improve efficiency, accuracy, and comprehensibility of the classification models in text labeling problems. …”
Get full text
Get full text
Get full text
Get full text