Search Results - (( developing voting based algorithm ) OR ( java data selection algorithm ))
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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 work employs MATLAB Neural Network Toolbox and Borland C++ programming language as the tools to develop the proposed system. The MLP networks are trained using two types of learning algorithm, which are the Levenberg Marquardt and the Resilient Back Propagation algorithms. …”
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Research Reports -
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Secure E-Voting With Blind Signature
Published 2003“…We have developed an electronic voting system, E-Voting for a general election. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Then canonical Polyadic decomposition-based attribute reduction is applied to the offload-able task to reduce the data size. Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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Classification of Mental Health Level of Students Using SMOTE and Soft Voting Ensemble Classifier and the DASS-21 Profile
“…It leverages the Synthetic Minority Over-sampling Technique (SMOTE) to address the class imbalance in the dataset and employs a Voting Ensemble with soft voting to combine several base algorithms (Logistic Regression, Random Forest, Gradient Boosting, and XGBoost/SVM) for accurate prediction of mental health levels (normal, mild, moderate, severe, very severe). …”
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A voting-based hybrid machine learning approach for fraudulent financial data classification / Kuldeep Kaur Ragbir Singh
Published 2019“…The voting-based hybrid approach consisting of various machine learning models with the ability to tackle issues related to missing and imbalanced data is then developed. …”
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An improved multiple classifier combination scheme for pattern classification
Published 2015“…The ant system (AS) algorithm is used to partition feature set in developing feature subsets which represent the number of classifiers. …”
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Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection
Published 2008“…The results also show that in Java, A Arraylist is the most suitable choice for storing Object and Arraylnt list is the most suitablec choice for storing integer data. …”
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Ant system and weighted voting method for multiple classifier systems
Published 2018“…A diverse classifier ensemble is constructed by training them with different feature set partitions. The ant system-based algorithm is used to form the optimal feature set partitions. …”
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Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection
Published 2008“…The results also show that in Java, A Arraylist is the most suitable choice for storing Object and Arraylnt list is the most suitablec choice for storing integer data. …”
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Making programmer effective for software development teams: An extended study
Published 2017“…Results emanated from training experiments were validated with Standard Voting (SV), Voting with Object tracking, and Naïve Bayes classification techniques based on prediction accuracy. …”
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Nearest neighbour group-based classification
Published 2010“…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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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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Reducing of Inconsistent Data using Fuzzy Multi Attribute Decision Making for Accessing Data from Database
Published 2013“…Sample data was selected for experiments purposes. The result indicates fuzzy multi attribute decision making is a suitable technique in reducing inconsistent data from database. …”
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TOPSIS-based Regression Algorithms Evaluation
Published 2022“…Following that, using three datasets, namely Combined Cycle Power Plant, Real Estate, and Concrete, Voting using multiple classifiers (k-means-based classifiers) was the top-ranked in the Combined Cycle Power Plant and Real Estate datasets. …”
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Image clustering comparison of two color segmentation techniques
Published 2010“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Smart thermal comfort system: a development of the fundamental control algorithm
Published 2004“…This paper reports on the development of the fundamental algorithm for a smart thermal comfort system. …”
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