Search Results - (( using evaluation method algorithm ) OR ( data classification system algorithm ))
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Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier
Published 2018“…There are two stages in the proposed classification system. Firstly, the 1D-LBP algorithm is used to extract the features of the normalized iris images and save the data in a text file according to the subject and the combinations to evaluate for the next stage. …”
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2
Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…The classification algorithm used in this research is the Convolutional Neural Network (CNN) algorithm. …”
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3
Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…Phase 2 is to study the performance of proposed integration system which using the data clustered to be used as train data for Naïve Bayes classifier. …”
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4
Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu
Published 2014“…The success evaluation of data mining classification algorithms have been realized through the data mining programs Weka and RapidMiner. …”
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5
Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…As a result, the highest average accuracy generated which is 96.91% by using WBCD dataset. The average accuracy of Bat Algorithm is comparing with other methods. …”
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Undergraduates Project Papers -
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Jogging activity recognition using k-NN algorithm
Published 2022“…Jogging activity recognition using the k-NN algorithm is a system that can help users collect information data of user speed movement using speed sensor and give the classification of jogging activity to the user. …”
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Classification Algorithms and Feature Selection Techniques for a Hybrid Diabetes Detection System
Published 2021“…K-nearest neighbor is used for classification of the diabetes dataset. …”
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Classification of JPEG files by using extreme learning machine
Published 2018“…Recovery of data files when their system information missing is a challenging research issue. …”
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Classification of credit card holder behavior using K Nearest Neighbor algorithm / Ahmad Faris Rahimi
Published 2017“…The third one is to evaluate the accuracy of the k Nearest Neighbors algorithm in the classification credit card holder behavior. …”
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10
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…An experimental analysis is conducted by several experiments to evaluate the performance of the proposed ensemble methods which has been tested on the 4 benchmark datasets, namely LingSpam, SpamAssassin, Spambase and CSDMC2010. …”
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11
Extreme learning machine classification of file clusters for evaluating content-based feature vectors
Published 2018“…Consequently, an Extreme Learning Machine (ELM) neural network algorithm is used to evaluate the performance of the three methods in which it classifies the class label of the feature vectors to JPEG and Non-JPEG images for files in different file formats. …”
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XCOA-MLP: Extended Coyote Optimization Algorithm for training neural networks in medical data classification
Published 2025“…This study proposes XCOA-MLP, a multilayer perceptron trained using an improved coyote optimization algorithm (XCOA). …”
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A novel framework for identifying twitter spam data using machine learning algorithms
Published 2020“…This study introduces a novel framework for identifying Twitter spam data based on machine learning algorithms. By initializing data pre-processing for clean-up, noise removal, and unpredictable unfinished data, reducing the number of features in the tweet dataset using mutual information is the study's methods. …”
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Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer
Published 2017“…Hence, reducing cost for other sensors, improving the analysis time for the classifier model building, and enhancing the productivity of the system at large. Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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15
Feature selection methods application towards a new dataset based on online student activities / Muhammad Hareez Mohd Zaki ... [et al.]
Published 2023“…The problem during the classification of students’ performance is the lack of factors used to identify and evaluate their performance. …”
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves
Published 2024“…In the next phase, the datasets are optimized using the Salp Swarm Algorithm (SSA), which improves classification accuracy. …”
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A novelty classification model for varied agarwood oil quality using the K-Nearest Neighbor algorithm / Aqib Fawwaz Mohd Amidon … [et al.]
Published 2022“…As a result, a new grading system based on artificial algorithms, namely K-Nearest Neighbor algorithms, was established. …”
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An Improve k-NN Classifier using Similarity Distance Plot-Data Reduction and Dask for Big Datasets
Published 2025“…The k-Nearest Neighbour (k-NN) algorithm is one of the most widely used Instance-Based Learning methods due to its simplicity and ease of implementation. …”
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Scene illumination classification based on histogram quartering of CIE-Y component
Published 2014“…This developed method finally will result in a high accuracy and straightforward classification system especially for illumination concept. …”
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Sentiment analysis of hotel reviews using Convolutional Neural Network / Sofea Aini Mohd Sufian
Published 2021“…So, the aim of this paper is to develop a prototype for hotel reviews using CNN Algorithm, to identify the requirements of CNN technique for text classification and also to evaluate the accuracy of CNN algorithm. …”
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