Search Results - (( using automatic method algorithm ) OR ( data classification modeling algorithm ))
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1
Fusion of moment invariant method and deep learning algorithm for COVID-19 classification
Published 2021“…The proposed method incorporates the MI-based features into the DL models using the cascade fusion method. …”
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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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3
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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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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5
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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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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Real-time classification improvement of Indonesian sign system letters (SIBI) using K-Nearest Neighbor algorithm
Published 2024“…A novel approach is introduced to enhance SIBI character predictions using the K-Nearest Neighbor (K-NN) algorithm. The K-NN algorithm is employed to predict the most suitable SIBI character based on the similarity of linguistic features between input speech and existing data. …”
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Multi-class classification automated machine learning for predicting earthquakes using global geomagnetic field data
Published 2025“…However, the complexity of the data has made it difficult to create an accurate model for EQ prediction using this method. …”
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Impact learning: A learning method from feature's impact and competition
Published 2023“…Machine learning algorithms build a model from sample data, called training data, to make predictions or judgments without being explicitly programmed to do so. …”
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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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11
Automated feature selection using boruta algorithm to detect mobile malware
Published 2020“…Boruta algorithm is used to select features automatically for assisting the machine learning. …”
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Impact learning : A learning method from feature’s impact and competition
Published 2023“…Machine learning algorithms build a model from sample data, called training data, to make predictions or judgments without being explicitly programmed to do so. …”
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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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14
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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15
Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration
Published 2014“…This article uses methodology based on chi-squared automatic interaction detection (CHAID), as a multivariate method that has an automatic classification capacity to analyse large numbers of landslide conditioning factors. …”
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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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17
Impact learning: A learning method from feature’s impact and competition
Published 2023“…Machine learning algorithms build a model from sample data, called training data, to make predictions or judgments without being explicitly programmed to do so. …”
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Autism spectrum self-stimulatory behaviours classification using explainable temporal coherency deep networks and SVM classifier / Liang Shuaibing
Published 2022“…Meanwhile, it is often difficult to obtain good classification results using unlabelled data, further research to train a model that can obtain good classification results and at the same time being practical will be valuable. …”
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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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Oil palm maturity classifier using spectrometer and machine learning
Published 2021“…The prediction was able to produce 100% accuracies by using Linear and Weighted KNN as classification testing algorithm. …”
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