Search Results - (( label classification (problems OR problem) algorithm ) OR ( using function method algorithm ))
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1
Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…Then a review of different methods currently available that can be used to solve clustering and classification problems is also given. …”
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2
Integrated Features by Administering the Support Vector Machine of Translational Initiations Sites in Alternative Polymorphic Context
Published 2012“…Many algorithms and methods have been proposed for classification problems in bioinformatics. …”
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3
Improving multi-resident activity recognition in smart home using multi label classification with adaptive profiling
Published 2018“…Furthermore, there is tendency that multi label classifications used instead of traditional single label classification technique. …”
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4
Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition
Published 2004“…The algorithm enhances the recognition ability of the system compared to manual extraction and labeling of pattern classes. …”
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5
Multi-label learning based on positive label correlations using predictive apriori
Published 2019“…Multi-label Learning (MLL) is a general task in data mining that consists of three main tasks: classification, label ranking, and multi-label ranking. …”
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6
Tracking and recognizing the activity of multi resident in smart home environments
Published 2017“…Also enable to foresee the patterns of everyday activities that commonly occur or not in an individual’s routine by considering the simplification and efficient method using the multi label classification framework. …”
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7
Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…In addition, the labelling is time consuming and done manually. To solve the problems mentioned, integration of unsupervised clustering algorithm and the supervised classifier is proposed. …”
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8
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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10
Multi label ranking based on positive pairwise correlations among labels
Published 2020“…Multi-Label Classification (MLC) is a general type of classification that has attracted many researchers in the last few years. …”
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11
Nearest neighbour group-based classification
Published 2010“…This can be seen as a simplification of the well studied, but computationally complex, non-sequential compound classifica�tion problem. In this paper, we extend three variants of the nearest neighbour algorithm to develop a number of non-parametric group-based classification techniques. …”
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12
Wavelet-Based Fractal Analysis of rs-fMRI for Classification of Alzheimer�s Disease
Published 2022“…This problem can be solved by using a better representation of neuronal activities provided by the connectivity of nonfractal components. …”
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13
Cyber parental control framework for objectionable web content classification and filtering based on topic modelling using enhanced latent dirichlet allocation / Hamza H. M. Altart...
Published 2023“…Despite substantial advancements in automating web classification that combines web mining and content classification methods, the study identifies a gap in applying advanced machine learning algorithms for superior objectionable web content classification. …”
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14
A direct ensemble classifier for learning imbalanced multiclass data
Published 2013“…Many real-world multiclass classification problems can be represented into a setting where non-crisp label need to be observed. …”
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15
Enhancing Classification Algorithms with Metaheuristic Technique
Published 2024“…For this reason, in this research,several auxiliary algorithms are introduced to improve the performance of the classification algorithm, namely the meta-heuristic algorithm. …”
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16
Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd
Published 2022“…One of the most powerful machine learning methods to handle classification problems is the decision tree. There are various decision tree algorithms, but the most commonly used are Iterative Dichotomiser 3 (ID3), CART, and C4.5. …”
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17
Visual codebook analysis in image understanding / Hoo Wai Lam
Published 2015“…As a resultant of that, visual codebook will learn wrong information, and thus affects the image classification performance. To deal with this problem, soft class labels are proposed in a way that both image level and patch level information are utilized. …”
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18
Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout
Published 2025“…Seven machine learning models—Artificial Neural Network (ANN), Random Forest (RF), Decision Tree (DTT), k-Nearest Neighbors (k-NN), Naïve Bayes (NB), Support Vector Machine (SVM), and Deep Neural Network (DNN)—were used for multi-label classification of the complications. The study employed two MLC frameworks: Problem Transformation methods (Binary Relevance, Classifier Chains, Label Power Set, and Calibrated Label Ranking) and Algorithm Adaptation. …”
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19
A modified weighted support vector machine (WSVM) to reduce noise data in classification problem
Published 2021“…Classification refers to a predictive modeling problem where a class label is predicted for a given example of input data. …”
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20
A modified weighted support vector machine (WSVM) to reduce noise data in classification problem
Published 2021“…Classification refers to a predictive modeling problem where a class label is predicted for a given example of input data. …”
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