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1
Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd
Published 2022“…Classification is a data mining technique used to classify varied data types according to a specific criterion. …”
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2
Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification
Published 2015“…Specifically, some selected benchmark classification problems are used. …”
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3
Accuracy assessment of Digital Terrain Model (DTM) Constructed Cloth Simulation Filter (CSF) and Multi Curvature Classification (MCC) algorithm on UAV LiDAR dataset / Mohamad Khair...
Published 2023“…Two algorithms, the Cloth Simulation Filter (CSF) in CloudCompare and the Multiscale Curvature Classification (MCC) in Global Mapper, were tested for this purpose. …”
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4
Deep learning object detector using a combination of Convolutional Neural Network (CNN) architecture (MiniVGGNet) and classic object detection algorithm
Published 2020“…MiniVGGNet is an architecture network used to train an object classification, and the data used for this purpose was collected from specific indoor environment building. …”
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5
Static hand gesture recognition using artificial neural network / Haitham Sabah Hasan
Published 2014“…Artificial neural network is built for the purpose of classification by using the back- propagation learning algorithm. …”
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6
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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7
Improved cuckoo search based neural network learning algorithms for data classification
Published 2014“…Specifically, 6 benchmark classification datasets are used for training the hybrid Artificial Neural Network algorithms. …”
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8
Improved intrusion detection algorithm based on TLBO and GA algorithms
Published 2021“…Optimization algorithms are widely used for the identification of intrusion. …”
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9
An improved directed random walk framework for cancer classification using gene expression data
Published 2020“…Sub-algorithms of SDW can be further divided into data pre-processing phase, specific tuning parameter selection, weight as additional variable, and exclusion of unwanted adjacency matrix. …”
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10
Predicting bankruptcy using ant colony optimization / Nur Syafiqah Abdul Ghani
Published 2021“…Data pre-processing method carries out certain computations such as data transformation (normalization, aggregation) to improve data quality. …”
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11
Scene illumination classification based on histogram quartering of CIE-Y component
Published 2014“…The result of categorization will be validated using inherent illumination data of scene. Applying the improving algorithm for characterizing histograms (histogram quartering) handed out the advantages of high accuracy. …”
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12
Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…An analysis of the choice of classification techniques is also required. Therefore, the LiDAR derived data were combined with WV-3 image using different fusion methods such as layer stacking (LS), Gram–Schmidt (GS), and PC spectral sharpening (PCSS). …”
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13
Input significance analysis: Feature selection through synaptic weights manipulation for EFuNNs classifier
Published 2017“…Specifically for the classification process, Big Data can cause the classifiers to process longer than necessary, and the redundant or irrelevant data may misguide the learning classification algorithms to learn the random error or noise related to them. …”
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14
Vader lexicon and support vector machine algorithm to detect customer sentiment orientation
Published 2023“…Methods: This study employs a method to compare the classification performance of the Vader lexicon annotation process with manual annotation. …”
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15
Classification of SNPs for obesity analysis using FARNeM modelling
Published 2013“…But, FARNeM did not achieve good reduction rate when applied to the experimental data set. However, the overall analysis showed that, it is encouraging to include feature selection process before the learning algorithms.…”
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16
A Novel Feature Selection Method for Classification of Medical Data Using Filters, Wrappers, and Embedded Approaches
Published 2022“…Furthermore, classification is then performed on selected features to classify the data using a support vector machine (SVM) classifier. …”
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17
Pathway-based analysis with Support Vector Machine (SVM-LASSO) for gene selection and classification
Published 2017“…Many methods have been done to address the issues of high data throughput due to increased use of microarray technology. …”
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18
K-gen phishguard: an ensemble approach for phishing detection with k-means and genetic algorithm
Published 2025“…In the second phase, the best set of features in each group is identified through the Genetic algorithm to enhance the classification process. Finally, a voting ensemble technique is applied, in which the Support Vector Machine (SVM), Random Forest (RF), Extreme Gradient Boosting (XGBoost) and Adaptive boosting (AdaBoost) models are combined. …”
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19
Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant
Published 2007“…Multi-layer perceptron (MLP) neural network trained using backpropagation algorithm is used to segment the color image. …”
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20
Six grades agarwood oil quality classification using K : nearest neighbour model of significant chemical compounds / Aqib Fawwaz Mohd Amidon
Published 2023“…Thus, this study proposes a novel classification technique for the agarwood oil quality grade using K-Nearest Neighbour (KNN) algorithm applied to selected chemical compound of the agarwood oil. …”
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