Search Results - (( using solution machine algorithm ) OR ( data classification mining algorithm ))

Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif by Jantan, Hamidah, Mat Yusof, Norazmah, Abdul Latif, Mohd Hanapi

“…Database or data warehouse is rich with hidden information that can be used to provide intelligent decision using data mining technique. …”
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Machine Learning Algorithms for Diabetes Prediction: A Review Paper by Al-Sideiri A., Cob Z.B.C., Drus S.B.M.

Logistic regression methods for classification of imbalanced data sets by Santi Puteri Rahayu, -

“…Classification of imbalanced data sets is one of the important researches in Data Mining community, since the data sets in many real-world problems mostly are imbalanced class distribution. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

“…As for classification, researchers have used semi-supervised learning for extreme learning machine (ELM), where they have exploited both the labeled and unlabeled data in order to boost the learning performances. …”
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Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction by Mohd Aris, Teh Noranis, Abu Bakar, Azuraliza, Mahiddin, Normadiah, Zolkepli, Maslina

“…Most computer applications use machine learning and data mining techniques to aid classification and prediction of a disease. …”
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Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO by Sharifah Sakinah, Syed Ahmad

“…Data reduction is an essential task in the data preparation phase of knowledge discovery and data mining (KDD). …”
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Sentiment analysis of customer review for Tina Arena Beauty by Amri, Nur Najwa Shahirah

“…The project followed the Cross-Industry Standard Process for Data Mining (CRISP- DM) methodology to ensure a structured implementation. …”
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DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH by LUONG, TRUNG TUAN

“…The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. …”
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Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu by Pala, Tuba, Camurcu, Ali Yilmaz

“…The success evaluation of data mining classification algorithms have been realized through the data mining programs Weka and RapidMiner. …”
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The application of neural network data mining algorithm into mixed pixel classification in geographic information system environment by Nanna Suryana, Herman

“…This , paper discusses the development of data mining and pattern recognition algorithm to handle the complexity of hyperspectral remote sensing images in Geographical Information Systems environment. …”
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Combining object-based classification and data mining algorithm to classify urban surface materials from worldview-2 satellite image by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi

“…In this study, Data Mining was performed using C4.5 algorithm to select the appropriate attributes for object-based classification. …”
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Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

“…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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A comparative study between rough and decision tree classifiers by Mohamad Mohsin, Mohamad Farhan

“…Theoretically, a good set of knowledge should provide good accuracy when dealing with new cases.Besides accuracy, a good rule set must also has a minimum number of rules and each rule should be short as possible.It is often that a rule set contains smaller quantity of rules but they usually have more conditions.An ideal model should be able to produces fewer, shorter rule and classify new data with good accuracy.Consequently, the quality and compact knowledge will contribute manager with a good decision model.Because of that, the search for appropriate data mining approach which can provide quality knowledge is important.Rough classifier (RC) and decision tree classifier (DTC) are categorized as RBC.The purpose of this study is to investigate the capability of RC and DTC in generating quality knowledge which leads to the good accuracy.To achieve that, both classifiers are compared based on four measurements that are accuracy of the classification, the number of rule, the length of rule, and the coverage of rule.Five dataset from UCI Machine Learning namely United States Congressional Voting Records, Credit Approval, Wisconsin Diagnostic Breast Cancer, Pima Indians Diabetes Database, and Vehicle Silhouettes are chosen as data experiment.All datasets were mined using RC toolkit namely ROSETTA while C4.5 algorithm in WEKA application was chosen as DTC rule generator.The experimental results indicated that both classifiers produced good classification result and had generated quality rule in different types of model – higher accuracy, fewer rule, shorter rule, and higher coverage.In term of accuracy, RC obtained higher accuracy in average while DTC significantly generated lower number of rule than RC.In term of rule length, RC produced compact and shorter rule than DTC and the length is not significantly different.Meanwhile, RC has better coverage than DTC.Final conclusion can be decided as follows “If the user interested at a variety of rule pattern with a good accuracy and the number of rule is not important, RC is the best solution whereas if the user looks for fewer nr, DTC might be the best choice”…”
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Comparison Performance of Qualitative Bankruptcy Classification based on Data Mining Algorithms by Nilam Nur Amir, Sjarif, Yee, Fang Lim, NurulHuda, Mohd Firdaus Azmi, Kamalia, Kamardin, Doris Wong, Hooi Ten, Hafiza, Abas, Mubarak-Ali, Al-Fahim

“…Knowledge discovery using data mining techniques are commonly applied in bankruptcy classification and prediction. …”
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Data Mining Analysis Of Chronic Kidney Disease (CKD) Level by Mohd Harizi, Muhammad Hafizam Afiq

“…Data mining analysis takes place in four stages: data pre-processing, data classification, classification of attributes by stages of CKD, and classification model verification using Microsoft Excel and Waikato Environmental for Knowledge Analysis (WEKA) version 3.8.5 software. …”
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Data mining techniques for transformer failure prediction model: A systematic literature review by Ravi N.N., Mohd Drus S., Krishnan P.S.

“…Classification (of information); Forecasting; Industrial electronics; Outages; Power transformers; Preventive maintenance; Classification algorithm; Data mining algorithm; Maintenance strategies; Performance measurements; Prediction techniques; Predictive maintenance; Systematic literature review; Transformer failure; Data mining…”

Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease by Che Hashim, Izrahayu

“…As the ALOS PALSAR-2 image was evaluated with dual-polarization (HH and HV), each digitized point has two distinct backscatter data with four severity levels (T0 to T3). The machine learning algorithm consistently performs well when presented with a well-balanced dataset. …”
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Analysis Of Failure In Offline English Alphabet Recognition With Data Mining Approach by Munnian, Ruthrakumar

“…Therefore, this study attempts a data mining approach to the analysis of failure in offline English alphabet recognition. …”
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Problem restructuring in interger programming for reduct searching by Ungku Chulan, Ungku Azmi Iskandar

“…In effect, they are very useful in generating rules when solving the classification problem that is inherent in data mining. …”
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An enhancement of classification technique based on rough set theory for intrusion detection system application by Noor Suhana, Sulaiman

“…Thus, to deal with huge dataset, data mining technique can be improved by introducing discretization algorithm to increase classification performance. …”
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