Search Results - (( using vectorization mining algorithm ) OR ( based classification modeling algorithm ))

Document classification based on kNN algorithm by term vector space reduction by Moldagulova A., Sulaiman R.B.

A new model for iris data set classification based on linear support vector machine parameter's optimization by Faiz Hussain, Zahraa, Ibraheem, Hind Raad, Alsajri, Mohammad, Ali, Ahmed Hussein, Mohd Arfian, Ismail, Shahreen, Kasim, Sutikno, Tole

“…One of the outstanding classifications methods in data mining is support vector machine classification (SVM). …”
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Improving sentiment reviews classification performance using support vector machine-fuzzy matching algorithm by Nurcahyawati, Vivine, Mustaffa, Zuriani

“…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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Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms by Sirajun Noor, Noor Azmiya

“…Whereas for the German Frankfurt dataset, best DM classification model was found using Random Forest algorithm with an accuracy of 98.77%.…”
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Arabic Speaker Identification System for Forensic Authentication Using K-NN Algorithm by Abdulwahid S., Mahmoud M.A., Abdulwahid N.

Data mining techniques for disease risk prediction model: A systematic literature review by Ahmad W.M.T.W., Ghani N.L.A., Drus S.M.

An Automated System For Classifying Conference Papers by Ngan, Seon Choon Han

“…This project is aimed to develop an automated web-based conference paper system for the manual process of assigning papers to reviewers by using classification models. …”
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Classification of Diabetes Mellitus using Ensemble Algorithms by Noor, N.A.B.S., Elamvazuthi, I., Yahya, N.

“…The objective of this study is to perform DM classification using various machine learning algorithms. …”
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Sentiment analysis on national cultural tourism using Linear Support Vector Machine (LSVM) / Nur Haida Hanna Samsuddin by Samsuddin, Nur Haida Hanna

“…The study will identify sentiment analysis tasks based on classification model. A classifier will be designed and developed which is Linear Support Vector Machine (LSVM). …”
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Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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Enhanced dimensionality reduction methods for classifying malaria vector dataset using decision tree by Arowolo, Micheal Olaolu, Adebiyi, Marion Olubunmi, Adebiyi, Ayodele Ariyo

“…The performances of the model are evaluated and validated using the classification accuracy to compare existing approaches in the literature. …”
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Named entity recognition using a new fuzzy support vector machine. by Mansouri, Alireza, Affendy, Lilly Suriani, Mamat, Ali

“…Some of the Machine learning algorithms used in NER methods are, support vector machine(SVM), Hidden Markov Model, Maximum Entropy Model (MEM) and Decision Tree. …”
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Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

“…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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Estimating 1-MCP application for Kampuchea guava with data mining technology by Ding, Phebe, Khor, Kor Chin

“…The classification models can then be used for estimating the 1-MCP application fast whenever there are new data available. …”
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A COMPARATIVE STUDY OF MACHINE LEARNING MODELS FOR PREDICTION OF AUTISM SPECTRUM DISORDER USING SCREENING DATA by Yeap, Ming Yue

“…The performance of the classification models for ASD will be compared. Finally, the best classification model for ASD prediction was a model trained using the Support Vector Machine (SVM) algorithm…”
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Combining cluster quality index and supervised learning to predict students’ academic performance by Suhaila Zainudin, Rapi’ah Ibrahim, Hafiz Mohd Sarim

“…Three classification algorithms have been selected: Logistic Regression (LR), Support Vector Machine (SVM) and Decision Tree (DT). …”
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An application of predicting student performance using kernel k-means and smooth support vector machine by Sajadin, Sembiring

“…In this study, psychometric factors used as predictor variables, thereare Interest, Study Behavior, Engaged Time, Believe, and Family Support.The rulemodel developed using Kernel K-means Clustering and Smooth Support Vector MachineClassification.Both of these techniquesbased on kernel methodsand relativelynew algorithms of data mining techniques, recently received increasingly popularity in machine learning community. …”
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Multitasking deep neural network models for Arabic dialect sentiment analysis by Alali, Muath Mohammad Oqlah

“…So far, there has been no effort to handle the negation context in Arabic using a deep neural network. The existing approaches are based on traditional machine learning algorithms, such as support vector machine (SVM). …”
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A Review on Predictive Model for Heart Disease using Wearable Devices Datasets by Mohd Syafiq Asyraf, Suhaimi, Nor Azuana, Ramli, Noryanti, Muhammad

“…Other approaches, such as Naive Bayes, Support Vector Machine, and Decision Tree algorithms, are used to analyze medical data sets to forecast cardiac disease. …”
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Risk prediction analysis for classifying type 2 diabetes occurrence using local dataset by Abd Rahman, M. Hafiz Fazren, Wan Salim, Wan Wardatul Amani, Abd-Wahab, Firdaus

“…Besides that, real world data are likely to be complex, incomplete and unorganized making it a challenge to develop models around it. This research aims to develop a robust prediction model for classification of type 2 diabetes mellitus (T2DM), with the interest of a Malaysian population, using several well-known machine learning algorithm such as Decision Tree, Support Vector Machine and Naïve Bayers. …”
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