Classification of tumor marker values using heuristic data mining methods

Author(s):  
Stephan M. Winkler ◽  
Michael Affenzeller ◽  
Witold Jacak ◽  
Herbert Stekel
2016 ◽  
Vol 51 (20) ◽  
pp. 2853-2862 ◽  
Author(s):  
Serkan Ballı

The aim of this study is to diagnose and classify the failure modes for two serial fastened sandwich composite plates using data mining techniques. The composite material used in the study was manufactured using glass fiber reinforced layer and aluminum sheets. Obtained results of previous experimental study for sandwich composite plates, which were mechanically fastened with two serial pins or bolts were used for classification of failure modes. Furthermore, experimental data from previous study consists of different geometrical parameters for various applied preload moments as 0 (pinned), 2, 3, 4, and 5 Nm (bolted). In this study, data mining methods were applied by using these geometrical parameters and pinned/bolted joint configurations. Therefore, three geometrical parameters and 100 test data were used for classification by utilizing support vector machine, Naive Bayes, K-Nearest Neighbors, Logistic Regression, and Random Forest methods. According to experiments, Random Forest method achieved better results than others and it was appropriate for diagnosing and classification of the failure modes. Performances of all data mining methods used were discussed in terms of accuracy and error ratios.


2011 ◽  
Vol 44 (2) ◽  
pp. e39-e40
Author(s):  
Maik Götze ◽  
Christian Wolff ◽  
Bernd Krause ◽  
Dietrich Romberg

2019 ◽  
Vol 77 (3) ◽  
pp. 349-363
Author(s):  
Citra Kurniawan ◽  
Punaji Setyosari ◽  
Waras Kamdi ◽  
Saida Ulfa

The purpose of this research was to build a classification model and to measure the correlation of self-efficacy with visual-verbal preferences using data mining methods. This research used the J48 classifier and linear projection method as an approach to see patterns of data distribution between self-efficacy and visual-verbal preferences. The measurement of the correlation of engineering students' self-efficacy with visual-verbal preferences using the data mining method approach gets the result that self-efficacy does not correlate with visual-verbal preferences. However, engineering students' self-efficacy influences the achievement of initial learning outcomes. Visual-verbal preference is more influenced by students' interest in images so it can be concluded that self-efficacy affects the initial results of learning but does not have a correlation with visual-verbal preferences. The results of the decision tree provide the results that are easily understood and present a correlation between self-efficacy and visual-verbal preferences in a visual form. Keywords: self-efficacy, visual-verbal preferences, data mining.


Currently in the community many who keep birds. To get the birds people are looking for in the bird market. Total species of birds traded (Kabupaten Cianjur) as many as 46 types of 23 tribes. From the search results were found by IUCN endangered bird species but by law in Indonesia excluding protected ones such as the species of ekelgeling (Cissathalassina) whose conservation status is highly endangered. The excavation of the rule based on available data using the c45 algorithm shows that the dominance status of bird species in the Cipanas area has a significant influence on the status of the dominance of bird species for the entire Cianjur region.


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