Search Results - (( _ relations ((a algorithm) OR (new algorithm)) ) OR ( data classification based algorithm ))*
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1
Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach
Published 2009“…In the current research, the new algorithm was tested and applied to the multiclass classification of two or more categories, which are important for handling problems related to practical classification. …”
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2
Case Slicing Technique for Feature Selection
Published 2004“…One of the problems addressed by machine learning is data classification. Finding a good classification algorithm is an important component of many data mining projects. …”
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3
An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani
Published 2015“…The urban growth images obtained are analysed to improve existing classification algorithms. The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. …”
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4
Ant colony optimization algorithm for rule based classification: Issues and potential
Published 2018“…This paper presents a review of related work of ACO rule classification which emphasizes the types of ACO algorithms and issues. …”
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5
Grid base classifier in comparison to nonparametric methods in multiclass classification
Published 2010“…In the current research, the new algorithm was tested and applied to the multiclass classification of two or more categories, which are important for handling problems related to practical classification. …”
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6
Adaptive parameter control strategy for ant-miner classification algorithm
Published 2020“…Pruning is the popular framework for preventing the dilemma of over fitting noisy data. This paper presents a new hybrid Ant-Miner classification algorithm and ant colony system (ACS), called ACS-Ant Miner. …”
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7
Design and analysis of management platform based on financial big data
Published 2023“…In order to make financial big data generate business value and improve the information application level of financial management, aiming at the high error rate of current financial data classification system, this article adopts the fuzzy clustering algorithm to classify financial data automatically, and adopts the local outlier factor algorithm with neighborhood relation (NLOF) to detect abnormal data. …”
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8
Utilisation of Exponential-Based Resource Allocation and Competition in Artificial Immune Recognition System
Published 2011“…Artificial Immune Recognition System is one of the several immune inspired algorithms that can be used to perform classification, a data mining task. …”
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9
An ensemble data summarization approach based on feature transformation to learning relational data
Published 2015“…A ensemble clustering is designed, used and evaluated to generate the final classification framework that will take all input generated from the GA based clustering with Feature Selection and Feature Construction algorithms and perform the classification task for the relational datasets. …”
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10
Optimized feature construction methods for data summarizations of relational data
Published 2014“…Dynamic Aggregation of Relational Attributes (DARA) algorithm is one of the approaches to summarize data stored in a target table that has a one-to-many relationship with data stored in a non-target table. …”
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11
Dimensionality reduction in data summarization approach to learning relational data
Published 2013“…Based on the experimental results, the DARA algorithm is proven to be very effective in learning relational data. …”
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Classification of left/right hand movement from EEG signal by intelligent algorithms
Published 2015“…Initial processing of the EEG signals has been carried out on 2 electrodes named C3 & C4; after that the bi-orthogonal wavelet coefficients, Welench Power Spectral Density estimates and the average power were used as a feature set for classification. We have given a relative study of currently used classification algorithms along with a new approach for classification i.e. …”
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Sentiment analysis of restaurant reviews in Kuala Terengganu based on K-Nearest Neighbor/ Siti Syazwana Jafri
Published 2021“…In the future, it is very recommended to experiment with different algorithm. The volume of data should be large as it can generate better result of classification method.…”
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14
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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15
Non-fiducial based electrocardiogram biometrics with kernel methods
Published 2017“…A new non-fiducial approach is proposed for feature extraction. …”
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16
Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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17
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The first research objective is to develop a new deep learning algorithm by a hybrid of DNN and K-Means Clustering algorithms for estimating the Lorenz chaotic system. …”
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18
Improved voting technique for ensemble of MLP system applied on various classification data / Saodah Omar, Iza Sazanita Isa and Junita Mohd Saleh.
Published 2010“…The most well-known ANN architecture is the Multilayer Perceptron (MLP) network which is widely used for solving problems related to data classifications. However, the conventional ANN theory selects the best MLP (after training) for classification based on one which has the least number of hidden neurons, and gives the highest percentage of correct classification when if there are other MLPs (with more number of hidden neurons) which gives the same highest percentage of correct classification. …”
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19
Sentiment analysis on national cultural tourism using Linear Support Vector Machine (LSVM) / Nur Haida Hanna Samsuddin
Published 2020“…In future, it is recommended to experiment with different algorithm or kernel of Support Vector Machine. The volume of data should be large as it can generate better result of classification method.…”
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20
An ensemble method with cost function on churn prediction
Published 2019“…Therefore, this paper aims to achieve higher classification accuracy and at the same time, minimising ensemble classifiers by constructing a new ensemble method based on dimensionality reduction in soft set theory. …”
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