Search Results - (( using vector based algorithm ) OR ( data classification using algorithm ))
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1
Enhanced ontology-based text classification algorithm for structurally organized documents
Published 2015“…The fourth and fifth algorithms, Concept Feature Vector_Text Classification (CFV_TC) and Structure Feature Vector_Text Classification (SFV_TC) classify the document to its related set of classes. …”
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2
Using the bees algorithm to optimise a support vector machine for wood defect classification
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3
Support directional shifting vector: A direction based machine learning classifier
Published 2021“…Supervised learning mainly deals with regression and classification. There exist several types of classification algorithms, and these are based on various bases. …”
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Document classification based on kNN algorithm by term vector space reduction
Published 2023Conference Paper -
5
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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6
Improving sentiment reviews classification performance using support vector machine-fuzzy matching algorithm
Published 2023“…Many of these dimensionalities have a major impact on the complexity and performance of the algorithms used for classification. Various challenges were encountered, including how to determine the optimal combination of pre-processing techniques, how to clean the dataset, and determine the best classification algorithm. …”
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7
Modified word representation vector based scalar weight for contextual text classification
Published 2024“…Based on the acquired results, the experiments reveal that the modified word vectors algorithm can effectively alter original LLM-generated word vectors to reflect intended contexts and can outperform baseline scores in contextual text classification tasks. …”
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8
Enhancing Classification Algorithms with Metaheuristic Technique
Published 2024“…Implementing this process uses classification algorithms such asNaïve Bayes, Support Vector Machine,and Random Forest. …”
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9
Thematic textual hadith classification: an experiment in rapidminer using support vector machine (SVM) and naïve bayes algorithm
Published 2020“…The classification for this thematic Hadith dataset is implemented using Rapidminer, a machine learning tool using Naïve Bayes and Support Vector Machine (SVM) methods. …”
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10
A comparison of support vector machine and decision tree classifications using satellite data of Langkawi Island
Published 2009“…The study indicates that the classification accuracy of SVM algorithm was better than DT algorithm. The overall accuracy of the SVM using four kernel types was above 73% and the overall accuracy of the DT method was 69%. …”
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11
Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…Many optimisation-based intrusion detection algorithms have been developed and are widely used for intrusion identification. …”
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12
A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition
Published 2002“…Classification rules were generated from training feature vectors set, and a modified form of the standard voter classification algorithm, that use the rough sets generated rules, was applied. …”
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13
SVM for network anomaly detection using ACO feature subset
Published 2016“…This paper proposes a detection model, ant system with support vector machine, which uses ant system, a variation of ant colony optimization, to filter out the redundant and irrelevant features for support vector machine classification algorithm. …”
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14
Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters
Published 2024“…The purpose of this study is to evaluate and compare the performance of these algorithms in terms of accuracy. The methodology used includes data collection, preprocessing, and algorithm implementation with evaluation using crossvalidation techniques. …”
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15
A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
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16
A new model for iris data set classification based on linear support vector machine parameter's optimization
Published 2020“…In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.…”
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17
Enhanced dimensionality reduction methods for classifying malaria vector dataset using decision tree
Published 2021“…RNA-Seq data are utilized for biological applications and decision making for classification of genes. …”
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18
Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms
Published 2021“…The objective of this study is to perform DM classification using various machine learning algorithms using Weka as a tool. …”
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Extreme learning machine classification of file clusters for evaluating content-based feature vectors
Published 2018“…Consequently, an Extreme Learning Machine (ELM) neural network algorithm is used to evaluate the performance of the three methods in which it classifies the class label of the feature vectors to JPEG and Non-JPEG images for files in different file formats. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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