Search Results - (( data classification using algorithm ) OR ( automatic classification modeling algorithm ))
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Sentiment analysis using negative selection algorithm for Twitter’s messages / Nazirah Che Alhadi
Published 2012“…In order to develop this model classification and prototype, 480 Twitter’s messages were used as training data and 120 Twitter’s messages for testing data to determine the accuracy of the classification model. …”
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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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Fusion of moment invariant method and deep learning algorithm for COVID-19 classification
Published 2021“…This paper proposes a fusion of a moment invariant (MI) method and a DL algorithm for feature extraction to address the instabilities in the existing COVID-19 classification models. …”
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A comparative study in classification techniques for unsupervised record linkage model
Published 2011“…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. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…A well known task is classification that predicts the class of new instances using known features or attributes automatically. …”
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Multi-class classification automated machine learning for predicting earthquakes using global geomagnetic field data
Published 2025“…Through statistical analysis, important features were extracted and a multi-class classification model using geomagnetic data was created. …”
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Identifying diseases and diagnosis using machine learning
Published 2023“…For classify the disease classification algorithms are used. It uses are many dimensionality reduction algorithms and classification algorithms. …”
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Analysing the performance of classification algorithms on diseases datasets
Published 2023“…The proposed classification algorithms measure the diseases using the disease datasets which estimates the accurate prediction. …”
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Machine learning application for concrete surface defects automatic damage classification
Published 2024“…This model is trained using 80% of the image data and tested using another 20% of the image data. …”
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An automatic grading model for semantic complexity of english texts using bidirectional attention-based autoencoder
Published 2024“…This paper first analyzes the importance of automatic classification of semantic complexity in English text, and then builds an autoencoder structure based on bidirectional attention, which captures bidirectional information in text, and then uses the autoencoder structure for feature extraction and dimension reduction, which further strengthens the model’s ability to capture semantic complexity. …”
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Improved personalised data modelling using parameter independent fuzzy weighted k-nearest neighbour for spatio/spectro-temporal data
Published 2021“…Upon exploration of the architecture, the weighted k-nearest neighbours algorithm used for the classification module is found to be prone to misclassification as it relies solely on the majority voting rule to determine the class for new data vector. …”
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Sentiment analysis for malay newspaper (SAMNews) using negative selection algorithm / Nur Amalina Redzuan
Published 2013“…In future, a comparative study on Artificial Immune System and other techniques or algorithms can be carried out to enhance the performance of the classification model.…”
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Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network
Published 2016“…First proposed algorithm is the combination of momentum algorithm with adaptive learning rate (ALR) algorithm, and second proposed algorithm is the combination of momentum algorithm with automatic learning rate selection (ALRS) algorithm. …”
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Comparison of meta-heuristic algorithms for fuzzy modelling of covid-19 illness’ severity classification
Published 2022“…The performance of the five meta-heuristic algorithms was evaluated using the COVID-19 symptoms dataset. …”
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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms
Published 2020“…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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Unsupervised classification of multi-class chart images: A comparison of customized CNNs and transfer learning techniques
Published 2025“…However, the automatic classification of chart images remains a significant challenge, particularly in the absence of labeled data. …”
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Object-based imagery analysis for automatic urban tree species detection using high resolution satellite image
Published 2016“…The method of maximum likelihood classification and support vector machines leads to the lowest classification accuracy since these algorithms extract only the spectral information of each pixel and consequently fail to utilize spatial, color and textural information.…”
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A novel ensemble decision tree-based CHi-squared Automatic Interaction Detection (CHAID) and multivariate logistic regression models in landslide susceptibility mapping
Published 2014“…An ensemble algorithm of data mining decision tree (DT)-based CHi-squared Automatic Interaction Detection (CHAID) is widely used for prediction analysis in variety of applications. …”
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Sentiment analysis for airline services on Twitter using deep learning with word embedding / Mawada Mohamed Nour El Daim El Khalifa
Published 2020“…The role of Sentiment Analysis (SA) is to classify people's opinions into different categories, such as positive and negative from text, using existing algorithms. However, existing approaches such as the Bag of Words (BOW) model is frequently used for text classification, where a document is mapped to a feature vector before the construction of the actual model, using machine learning techniques, like Logistical Regression and Support Vector algorithms. …”
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