Search Results - (( using codification based algorithm ) OR ( data evaluation mining algorithm ))

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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Evaluation of data mining models for predicting concrete strength by Wong, Chuan Ming

“…Data mining techniques are becoming more popular in recent years due to their abilities to predict any types of data with high accuracy. …”
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Tree-based contrast subspace mining method by Florence Sia Fui Sze

“…The research works involve first preparing the real world numerical and categorical data sets. Then, the tree-based method, the genetic algorithm based parameter values identification of tree-based method, and followed by the genetic algorithm based tree-based method, for numerical data sets are developed and evaluated. …”
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An efficient algorithm to discover large and frequent itemset in high dimensional data by Zulkurnain, Nurul Fariza

“…Mining these data produces an explosive number of smaller itemsets which are less important than colossal (large) ones. …”
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Evaluation and optimization of frequent association rule based classification by Izwan Nizal Mohd Shaharanee, Jastini Jamil

“…In this paper, a systematic way to evaluate the association rules discovered from frequent itemset mining algorithms, combining common data mining and statistical interestingness measures, and outline an appropriated sequence of usage is presented. …”
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Evaluation of the Effect of Ideological and Political Education on Psychological Crisis Intervention for University Students Based on Data Mining Algorithm by Hexia Yao, Mohd. Dahlan Hj. A. Malek

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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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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.

“…Decision making; Decision trees; Forecasting; Health care; Soft computing; Accuracy evaluation; Classification technique; Data mining algorithm; Descriptive analysis; Disease risks; Infectious disease; Risk prediction models; Systematic literature review; Data mining…”

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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An Improved C4.5 Data Mining Driven Algorithm for the Diagnosis of Coronary Artery Disease by Haruna, A.A., Muhammad, L.J., Yahaya, B.Z., Garba, E.J., Oye, N.D., Jung, L.T.

“…This research used an im-proved C4.5 data mining algorithm for the diagnosis of CAD. A performance evaluation of the improved algorithm was carried out against the traditional C4.5 Algorithm. …”
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Comparing the performance of FCBF, Chi-Square and relief-F filter feature selection algorithms in educational data mining by Zaffar, M., Hashmani, M.A., Savita, K.S.

“…Educational Data Mining (EDM) is a very vital area of Data Mining, and it is helpful in predicting the performance of students. …”
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Comparing the performance of FCBF, Chi-Square and relief-F filter feature selection algorithms in educational data mining by Zaffar, M., Hashmani, M.A., Savita, K.S.

“…Educational Data Mining (EDM) is a very vital area of Data Mining, and it is helpful in predicting the performance of students. …”
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Prime-based method for interactive mining of frequent patterns by Nadimi-Shahraki, Mohammad-Hossein

“…Moreover, this study introduces a mining algorithm called PC-miner to mine the mining model frequently with various values of minsup. …”
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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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Predicting future sales using genetic algorithm: data mining sales / Siti Hajar Yaacob by Yaacob, Siti Hajar

“…The objectives of this research are data mining are used to extract useful data from sales and product. …”
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Data mining based damage identification using imperialist competitive algorithm and artificial neural network by Gordan, Meisam, Razak, Hashim Abdul, Ismail, Zubaidah, Ghaedi, Khaled

“…In this study, to predict the damage severity of sin-gle-point damage scenarios of I-beam structures a data mining based damage identification framework and a hybrid algorithm combining Artificial Neural Network (ANN) and Imperial Competitive Algorithm (ICA), called ICA-ANN method, is proposed. …”
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Medical diagnosis using data mining techniques / Shaiful Nizam Zamri by Shaiful Nizam , Zamri

“…The report will firstly cover the inductors of data mining and the overview of the overall system and it also reviewed about the data mining paradigm. …”
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Rough-Set-and-Genetic-Algorithm based data mining and Rule Quality Measure to hypothesize distance protective relay operation characteristics from relay event report by Othman, Mohammad Lutfi, Aris, Ishak, Othman, Mohammad Ridzal, Osman, Harussaleh

“…Firstly, the data mining approach of the integrated-Rough-Set-and-Genetic-Algorithm is used to discover the relay CD-decision algorithm. …”
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A multi-layer dimension reduction algorithm for text mining of news in forex / Arman Khadjeh Nassirtoussi by Nassirtoussi, Arman Khadjeh

“…Every context requires its own customized text mining algorithms in order to achieve best results. …”
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Evaluation and optimization of frequent, closed and maximal association rule based classification by Mohd Shaharanee, Izwan Nizal, Hadzic, Fedja

“…Real world applications of association rule mining have well-known problems of discovering a large number of rules, many of which are not interesting or useful for the application at hand.The algorithms for closed and maximal item sets mining significantly reduce the volume of rules discovered and complexity associated with the task, but the implications of their use and important differences with respect to the generalization power, precision and recall when used in the classification problem have not been examined.In this paper, we present a systematic evaluation of the association rules discovered from frequent, closed and maximal item set mining algorithms, combining common data mining and statistical interestingness measures, and outline an appropriate sequence of usage.The experiments are performed using a number of real-world datasets that represent diverse characteristics of data/items, and detailed evaluation of rule sets is provided as a whole and w.r.t individual classes. …”
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