Search Results - (( user evaluation from algorithm ) OR ( label classification using algorithm ))
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Classification and visualization on eligibility rate of applicant’s LinkedIn account using Naïve Bayes / Nurul Atirah Ahmad
Published 2023“…This project implements the Naive Bayes algorithm as the classification algorithm. The collected data from LinkedIn profiles then undergoes data preprocessing. …”
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A hierarchical deep convolutional neural network for asphalt pavement crack detection and classification / Nor Aizam Muhamed Yusof
Published 2021“…The CrackLabel utilises a special design image thresholding algorithm known as Global and Lower Quartile Average Intensity (GLQAI). …”
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3
Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…The comparison results show that, the clusters labelled by the cluster labelling algorithm were the same as using co-spectral plot. …”
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A web-based image recognition system for detecting harumanis mangoes / Mohamad Shahmil Saari, Romiza Md Nor and Huzaifah A Hamid
Published 2020“…Furthermore, the accuracy of the image classification can be improved by increasing the number of datasets, the distance of images from the camera, and the labelling process. …”
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Exploring classification for sentiment analysis from halal based tweets
Published 2021“…It usually assigns a polarity of “positive”, “negative” or “neutral”. It uses an algorithmic technique to capture people's thoughts, sentiments, and emotions by incorporating Natural Language Processing and Machine Learning technology. …”
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Comparative analysis of text classification algorithms for automated labelling of quranic verses
Published 2017“…In this paper, we propose to automate the labelling task of the Quranic verse using text classification algorithms. …”
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A coherent knowledge-driven deep learning model for idiomatic - aware sentiment analysis of unstructured text using Bert transformer
Published 2023“…Sentiment analysis algorithms used to classify the sentiment of tweets on social media platforms such as Twitter face challenges when dealing with idiomatic expressions and figurative language used by users. …”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…As the result, the pattern classification accuracy is also xii increase. For examples, after applying the proposed integration system, the classification accuracy of Fisher’s Iris, Wine and Bacteria18Class has been increased from 88.67% to 96.00%, from 78.33% to 83.45% and from 93.33% to 94.67% respectively as compared to only used unsupervised clustering algorithm. …”
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An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…An investigative study was undertaken to assess the efficiency of EB and EW by evaluating their classification performance using Naive Bayes and K-nearest neighbor algorithms on four continuous datasets sourced from the UCI datasets. …”
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An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…An investigative study was undertaken to assess the efficiency of EB and EW by evaluating their classification performance using Naive Bayes and K-nearest neighbor algorithms on four continuous datasets sourced from the UCI datasets. …”
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Postal address handwritten recognition using convolutional neural network / Nur Hasyimah Abd Aziz
Published 2020“…CNN was chosen as an algorithm for classification task because various studies had concluded that it is able to produce highly accurate result. …”
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13
Multi label ranking based on positive pairwise correlations among labels
Published 2020“…Multi-Label Classification (MLC) is a general type of classification that has attracted many researchers in the last few years. …”
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Enhancing Classification Algorithms with Metaheuristic Technique
Published 2024“…Implementing this process uses classification algorithms such asNaïve Bayes, Support Vector Machine,and Random Forest. …”
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Performances of machine learning algorithms for binary classification of network anomaly detection system
Published 2018“…Moreover, network anomaly detection using machine learning faced difficulty when dealing the involvement of dataset where the number of labelled network dataset is very few in public and this caused many researchers keep used the most commonly network dataset (KDDCup99) which is not relevant to employ the machine learning (ML) algorithms for a classification. …”
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Fuzzy classification based on combinative algorithms with fuzzy similarity measure / Nur Amira Mat Saffie
Published 2019“…Furthermore, most classification algorithms, using either fuzzy or non-fuzzy approaches, produce results in the form of crisp or categorical classification outcomes. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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The classification of FTIR plastic bag spectra via label spreading and stacking
Published 2021“…Four pipelines were investigated, consisting of two machine learning algorithms, a stacked model that stacks the KNN, SVM and RF algorithms together, and Label spreading, as well as two different dimensionality reduction methods namely; SVD and UMAP. …”
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Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…Samples in the same cluster have the same label. The aim of data classification is to set up rules for the classification of some observations that the classes of data are supposed to be known. …”
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