Search Results - (( based estimation method algorithm ) OR ( data classification problem algorithm ))
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1
Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data
Published 2022“…However, in practice, high leverage points may lead to misleading results in solving variable selection problems. Therefore, a robust sure independence screening procedure based on the weighted correlation algorithm of MRFCH for high dimensional data is developed to address this problem. …”
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2
Thematic textual hadith classification: an experiment in rapidminer using support vector machine (SVM) and naïve bayes algorithm
Published 2020“…We believe that the result could be better by improving the data, algorithms, algorithm tuning or ensemble methods for the future experiments…”
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3
Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm
Published 2018“…Hence, We proposed interquartile range which is more resistance against outliers in data pre-processing. It shows that the IQR-HEOM method is more efficient to rectify the problem caused by using range in HEOM. …”
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4
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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5
Tree-based contrast subspace mining method
Published 2020“…The research works involve first preparing the real world numerical and categorical data sets. Then, the tree-based method, the genetic algorithm based parameter values identification of tree-based method, and followed by the genetic algorithm based tree-based method, for numerical data sets are developed and evaluated. …”
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6
A direct ensemble classifier for learning imbalanced multiclass data
Published 2013“…In this thesis, the problem of learning from imbalanced multiclass data classification is studied. …”
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7
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…Lastly, a new hybrid technique suggests tackling the current image encryption application problem by using the estimated parameters of chaotic systems with an optimization algorithm, the SKF algorithm. …”
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8
A modified reweighted fast consistent and high-breakdown estimator for high-dimensional datasets
Published 2024“…Thus, the new proposed algorithm can be applied to solve the problem of regression outliers in high-dimensional data (HDD) and serve as a better alternative to the minimum regularized covariance determinant (MRCD) estimator. © 2024 The Author(s)…”
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A comparative study and simulation of object tracking algorithms
Published 2020“…This article introduces the popular object tracking algorithms, from common problems in object tracking to the classification of algorithms: Early classic trackingalgorithms, tracking algorithms based on kernel correlation filtering, and tracking algorithms based on deep learning. …”
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10
Robust techniques for linear regression with multicollinearity and outliers
Published 2016“…Hence, we propose a new estimation method namely the modified GM-estimator (MGM) based on MGDFF. …”
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11
Plant recognition based on identification of leaf image using image processing / Nor Silawati Sha’ari
Published 2018“…NN such as Artificial Neural Network (ANN) and K-Nearest Neighbor (KNN) is trained in developing a classification system for agriculture purpose. ANN and KNN is applied to solve the problems in image analysis, pattern recognition and classification. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…To enhance the selection of most highly ranking features, irrelevant features are ‘pruned’ based on determined boundary threshold. In order to estimate the quality of ‘pruned’ features, self-adaptive DE algorithm is proposed. …”
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13
Adaptive Similarity Component Analysis in Nonparametric Dynamic Environment
Published 2011“…Data arrives from operational field in a stream model and similarity-based classification algorithms must identify them with acceptable performance. …”
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14
Bayesian Framework based Brain Source Localization Using High SNR EEG Data
Published 2019“…This research work discusses the results based on synthetically generated EEG data at an SNR level of 12 dB with Gaussian noise added linearly in data matrix. …”
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15
A comparative study of supervised machine learning approaches for slope failure production
Published 2023“…Generally, slope failure can be estimated based on traditional methods such as limit equilibrium method (LEM) or finite equilibrium method (FEM). …”
Conference Paper -
16
Dengue classification system using clonal selection algorithm / Karimah Mohd
Published 2012“…This project focused on three main objectives: to investigate dengue data and Clonal Selection Algorithm for classification of Dengue, to design and develops Clonal Selection Classification System (CSCS) and to evaluate Clonal Selection Classification System symptoms. …”
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17
Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd
Published 2022“…The study verified that the FID3-DBD algorithm could classify the continuous data, and the BFID3-DBD algorithm overcame the overfitting issue, reduced high variance, and increased test data classification accuracy.…”
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18
An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…This paper addresses the classification problem in machine learning focusing on predicting class labels for datasets with continuous features. …”
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An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…This paper addresses the classification problem in machine learning, focusing on predicting class labels for datasets with continuous features. …”
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A derivative-free optimization method for solving classification problem
Published 2010“…Problem statement: The aim of data classification is to establish rules for the classification of some observations assuming that we have a database, which includes of at least two classes. …”
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