Search Results - (( parallel optimization sensor algorithm ) OR ( quality classification mining algorithm ))

Data mining approach to herbs classification by Ahmad Dali, Adillah Dayana, Omar, Nurul Aswa, Mustapha, Aida

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MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM by Aurangzeb, khan, Baharum, Baharudin, Khairullah, khan

“…In this paper we proposed an algorithm for mining patterns of huge stock data to predict factors affecting the sale of products. …”
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Graduates employment classification using data mining approach by Ab Aziz, Mohd Tajul Rizal, Yusof, Yuhanis

“…Data Mining is a platform to extract hidden knowledge in a collection of data.This study investigates the suitable classification model to classify graduates employment for one of the MARA Professional College (KPM) in Malaysia.The aim is to classify the graduates into either as employed, unemployed or further study.Five data mining algorithms offered in WEKA were used; Naïve Bayes, Logistic regression, Multilayer perceptron, k-nearest neighbor and Decision tree J48.Based on the obtained result, it is learned that the Logistic regression produces the highest classification accuracy which is at 92.5%. …”
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MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM by Aurangzeb, khan, Baharum, Baharudin, Khairullah, Khan

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Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer by Tuerxun, Adilijiang

“…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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Estimating 1-MCP application for Kampuchea guava with data mining technology by Ding, Phebe, Khor, Kor Chin

“…In this preliminary study, data mining (DM) technology was utilized to achieve fast estimation of 1-MCP application based on different qualities of 'Kampuchea' Guava. …”
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Evaluation and optimization of frequent, closed and maximal association rule based classification by Mohd Shaharanee, Izwan Nizal, Hadzic, Fedja

“…With closed itemset mining already being a preferred choice for complexity and redundancy reduction during rule generation, this study has further confirmed that overall closed itemset based association rules are also of better quality in terms of classification precision and recall, and precision and recall on individual class examples. …”
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An adaptive ant colony optimization algorithm for rule-based classification by Al-Behadili, Hayder Naser Khraibet

“…Various classification algorithms have been developed to produce classification models with high accuracy. …”
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Intent-IQ: customer’s reviews intent recognition using random forest algorithm by Mazlan, Nur Farahnisrin, Ibrahim Teo, Noor Hasimah

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Improved building roof type classification using correlation-based feature selection and gain ratio algorithms by Norman, M., Mohd Shafri, Helmi Zulhaidi, Pradhan, Biswajeet, Yusuf, B.

“…Of late, application of data mining for pattern recognition and feature classification is fast becoming an essential technique in remote sensing research. …”
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Propositional satisfiability method in rough classification modeling for data mining by Abu Bakar, Azuraliza

“…The classification accuracy, the number of rules and the maximum length of rules obtained from the SIPIDRIP method was compared with other rough set method such as Genetic Algorithm (GA), Johnson, Holte l R, Dynamic and Exhaustive method. …”
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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

“…This study employs a combination of data mining tasks, such as clustering and classification, to undertake the prediction task. …”
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Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system by Nurnajmin Qasrina Ann, Ayop Azmi

“…Stereo vision sensor consists of two stereo cameras, mounted parallel in stationary position. …”
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Rough set discretization: equal frequency binning, entropy/MDL and semi naives algorithms of intrusion detection system by Noor Suhana, Sulaiman, Rohani, Abu Bakar

“…Discretization part is also the crucial part resulting the good classification. Empirical results have shown that the quality of classification methods depends on the discretization algorithm in preprocessing step. …”
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Rough set discretization: Equal frequency binning, entropy/MDL and semi naives algorithms of intrusion detection system by Noor Suhana, Sulaiman, Rohani, Abu Bakar

“…Discretization part is also the crucial part resulting the good classification. Empirical results have shown that the quality of classification methods depends on the discretization algorithm in preprocessing step. …”
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Rough Set Discretization: Equal Frequency Binning, Entropy/MDL and Semi Naives Algorithms of Intrusion Detection System by Noor Suhana, Sulaiman, Rohani, Abu Bakar

“…Discretization part is also the crucial part resulting the good classification. Empirical results have shown that the quality of classification methods depends on the discretization algorithm in preprocessing step. …”
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Running-Related Injury Classification For Professional Runners by Lingam, Darwineswaran Raja

“…This study aims to investigate the qualities of RRI dataset for reliable running-injury classification analysis with WEKA and also to establish an appropriate classification model for RRI in professional runners. …”
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Parallel execution of distributed SVM using MPI (CoDLib) by Salleh N.S.M., Suliman A., Ahmad A.R.

“…Support Vector Machine (SVM) is an efficient data mining approach for data classification. However, SVM algorithm requires very large memory requirement and computational time to deal with very large dataset. …”

A study of feature selection algorithms for predicting students academic performance by Zaffar, M., Savita, K.S., Hashmani, M.A., Rizvi, S.S.H.

“…In the light of this mentioned fact, it is necessary to choose a feature selection algorithm carefully. This paper presents an analysis of the performance of filter feature selection algorithms and classification algorithms on two different student datasets. …”
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A study of feature selection algorithms for predicting students academic performance by Zaffar, M., Savita, K.S., Hashmani, M.A., Rizvi, S.S.H.

“…In the light of this mentioned fact, it is necessary to choose a feature selection algorithm carefully. This paper presents an analysis of the performance of filter feature selection algorithms and classification algorithms on two different student datasets. …”
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