Search Results - (( pattern classification mining algorithm ) OR ( using a method algorithm ))
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1
A numerical method for frequent pattern mining
Published 2009“…In this paper, an efficient numerical method for mining frequent patterns is proposed. This method is based on prime number characteristics to generate all frequent patterns by using maximal frequent ones. …”
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2
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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3
First Semester Computer Science Students’ Academic Performances Analysis by Using Data Mining Classification Algorithms
Published 2014“…The comparative analysis is also conducted to discover the best classification model for prediction. From the experiment, the models develop using Rule Based and Decision Tree algorithm shows the best result compared to the model develop from the Naïve Bayes algorithm. …”
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4
Analysis Of Failure In Offline English Alphabet Recognition With Data Mining Approach
Published 2019“…Classification analysis was initially performed on all seven classifier’s algorithms at 10-fold dross validation mode. …”
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5
Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…Based on the experiment results, the classification method using the TIP approach has successfully performed rules generation and classification tasks as required during a classification operation. …”
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6
A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…Various data mining techniques are being used by researchers of different domains to analyze data and extract valuable information from a data set for further use. …”
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7
Lexicon-based and immune system based learning methods in Twitter sentiment analysis
Published 2016“…The aim of this article attempts to study the potential of this method in text classification for sentiment analysis.This study consists of three phases; data preparation; classification model development using three selected Immune System based algorithms i.e. …”
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8
Improved GART neural network model for pattern classification and rule extraction with application to power systems
Published 2023Subjects:Article -
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Classifying Indian Classical Dances By Motion Posture Patterns
Published 2019“…RandomForest algorithm returned the highest classification accuracy (99.2616%). …”
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10
A new model for iris data set classification based on linear support vector machine parameter's optimization
Published 2020“…One of the outstanding classifications methods in data mining is support vector machine classification (SVM). …”
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Data mining techniques for disease risk prediction model: A systematic literature review
Published 2023Conference Paper -
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Intuitive Content Management System to Preferences Template Throughout Data Collection by using Data Mining Classification of Prediction Method
Published 2016“…Data mining is a process to analyse patterns and models for all kinds of data. …”
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13
Setting up a new Radiology Center Technology for improvement : Data mining (Image Mining Technique)
Published 2016“…Data mining requires the use of data analysis tool containing statistical model, mathematical algorithms and machine learning methods to determine previously unknown, valid patterns and relationships in huge volume data. …”
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14
Classification of cervical cancer using random forest
Published 2022“…In this research, the cervical cancer risk classification model was used by using data mining approach which consider Decision Tree and Random Forest algorithm. …”
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15
Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…In this study we show how to apply a particular class of optimization methods known as pattern search methods to address these challenges. …”
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16
Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan
Published 2020“…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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17
Classification Of Gender Using Global Level Features In Fingerprint For Malaysian Population
Published 2016“…A new approach of algorithm based on the Mark Acree’s theory, focusing on fingerprint global extracted features is proposed and implemented for enhancing gender classification method. …”
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18
Forecast of Muslimah fashion trends in Caca's company / Muhammad Saifullah Mohd Taip
Published 2023“…The results showed that the decision tree algorithm had a higher accuracy of 100% for category prediction, 47% for colour prediction, and 65% for size prediction, while the random forest algorithm had a higher accuracy of 100% for category prediction, 85% for colour prediction, and 91% for size prediction. …”
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19
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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20
Enhancement of text representation for Indonesian document summarization with deep sequential pattern mining
Published 2023“…Therefore, the present study aims: (1) to improve Indonesian text summary by enhancing the Sequence of Word (SoW) as text representation using Sequential Pattern Mining (SPM) with PrefixSpan algorithm since the effectiveness of SPM in Indonesian is proven useful for text classification and clustering; (2) to combine SPM and Deep Learning (DeepSPM) in text summarization with Indonesian text, as a result of its superior accuracy when trained with large amounts of data; and (3) to evaluate the readability of Indonesian text summary with several evaluation scenarios. …”
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