Search Results - (( data 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“…The simulation study results and real data sets indicate that the proposed MRFCHCS+LAD-SCAD estimator was found to be the best method compared to other methods in this study.…”
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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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Article -
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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
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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5
Analysis of multicomponent transient signals using music superresolution technique
Published 2008“…A noisy multiexponential signal is subjected to a preprocessing procedure consisting of Gardeners' transformation and inverse filtering. Modified MUSIC algorithm is then applied to the deconvolved data. …”
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Proceeding Paper -
6
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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7
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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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 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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An Analysis of Large Data Classification using Ensemble Neural Network
Published 2017“…The estimates derived using Apriori method shows that proposed ensemble ANN algorithm with a different approach is feasible where such problem with a high number of inputs and classes can be solved with time complexity of O(n^k ) for some k, which is a type of polynomial. …”
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Conference or Workshop Item -
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Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data
Published 2018“…The modification comprises of two main modelling problems: high-dimensionality and missing data. These problems were extensively studied within the scope of classification (binary and multi-class) and regression (linear and survival). …”
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12
Robust techniques for linear regression with multicollinearity and outliers
Published 2016“…The proposed method is formulated by incorporating robust MM-estimator and the modified generalized M-estimator (MGM) in the LRR algorithm. …”
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13
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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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…In order to improve recognition of high interclass similarity activities, One-Versus- All (OVA) binarization strategy is introduced by transforming original multi-class classification problems into a series of two-class classification problems. …”
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15
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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Student Project -
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Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions
Published 2019“…These sensors are pre-processed and different feature sets such as time domain, frequency domain, wavelet transform are extracted and transform using machine learning algorithm for human activity classification and monitoring. …”
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Article -
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Bayesian Framework based Brain Source Localization Using High SNR EEG Data
Published 2019“…Furthermore, the solution of inverse problem is realized through usage of various optimization techniques such as minimum norm estimation (MNE), low resolution brain electromagnetic tomography (LORETA), multiple signal classification (MUSIC) and multiple sparse priors (MSP). …”
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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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Fuzzy C means imputation of missing values with ant colony optimization
Published 2020“…This error should be handled correctly before data is processed into processing model. This paper proposes a improved method of imputation by employing a new version of Fuzzy c Means (FCM) which hybridized with Evolutionary Algorithm to handle missing values problem. …”
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