Search Results - (( data classification method algorithm ) OR ( data extraction method algorithm ))
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1
Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…This research compares three different methods for extracting features from fruit images to determine which method yields the highest accuracy for fruit classification. …”
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2
Text Extraction Algorithm for Web Text Classification
Published 2010“…The experimental results show that Naive-Bayes classifier with web text extraction algorithm proves to be the best method for web text classification.…”
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3
Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier
Published 2018“…There are a lot of feature extraction methods and classification methods for iris classification. …”
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4
An efficient algorithm for cardiac arrhythmia classification using ensemble of depthwise Separable convolutional neural networks
Published 2020“…No preprocessing method was required while feature extraction was combined with classification. …”
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5
A new ant based rule extraction algorithm for web classification
Published 2011“…Methods to reduce the number of attributes and discretization are two important data pre-processing steps before the data can be used for classification activity. …”
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6
Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…Whereas for supervised learning method, it requires teacher or prior data (i.e. large, prohibitive and labelled training data) during classification process which in real life, the cost of obtaining sufficient labelled training data is high. …”
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7
Breast cancer disease classification using fuzzy-ID3 algorithm with FUZZYDBD method: automatic fuzzy database definition
Published 2021“…This study aims to resolve the limitation of an existing method, ID3 algorithm that unable to classify the continuous-valued data and increase the classification accuracy of the decision tree. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…Methods for improving supervised and unsupervised classification of remotely sensed data were developed in this study. …”
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9
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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Pattern Recognition for Human Diseases Classification in Spectral Analysis
Published 2022“…Typically, pattern recognition consists of two components: exploratory data analysis and classification method. Exploratory data analysis is an approach that involves detecting anomalies in data, extracting essential variables, and revealing the data’s underlying structure. …”
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11
Utilizing artificial bee colony algorithm as feature selection method in Arabic text classification
Published 2023“…In this paper, the filter method chi square and the Artificial Bee Colony) ABC algorithm were both used as FS methods . …”
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A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…Many researchers, who have developed methods and algorithms within the field of artificial intelligence, machine learning and data mining, have addressed extracting useful information from the data. …”
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13
An Ar Natural Marker Similarities Measurement Algorithm For E-Biodiversity
Published 2018“…The objective of this research is to comparatively evaluate the effectiveness of different algorithms, method combination procedure, and their parameters towards classification accuracy. …”
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14
Genetic algorithm based ensemble framework for sentiment analysis
Published 2018“…Machine Learning classification is commonly used in sentiment analysis and it requires plain text documents to be transformed to analyzable data through feature extraction and selection. …”
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15
Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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16
Efficient classifying and indexing for large iris database based on enhanced clustering method
Published 2018“…From the experimental results, the proposed method was indeed more effective for clustering and classification and outperformed the traditional k-mean algorithm. …”
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Enhancing benthic habitat mapping: A review of integrating satellite and side scan sonar data for improved classification accuracy
Published 2024“…Research on classification methods shows that object-based approaches produce different results depending on field conditions, which are consistently better than pixel-based methods, for both satellite spectral and side-scan sonar data. …”
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The classification of motor imagery response: an accuracy enhancement through the ensemble of random subspace k-NN
Published 2021“…In comparison with other classification approaches reported in the recent studies, the proposed method enhanced the accuracy by 2.09% for data-1, 1.29% for data-2, 4.95% for data-3 and 5.71% for data-4, respectively. …”
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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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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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