Imbalanced classification of manufacturing quality conditions using cost-sensitive decision tree ensembles

Kim, Ae-Kyung; Oh, Kyuhyup; Jung, Jae‐Yoon; Kim, Bohyun

doi:10.1080/0951192x.2017.1407447

Cited by 48 publications

(18 citation statements)

References 46 publications

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“…The J48 algorithm has been widely used to study problems in the manufacturing area related to quality improvement in production processes [10,22]. In this work, the J48 generated models that classified training dataset data very well.…”

Section: Discussionmentioning

confidence: 99%

Decision Tree Methods for Predicting Surface Roughness in Fused Deposition Modeling Parts

Barrios

Romero

2019

Materials

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3D printing using fused deposition modeling (FDM) includes a multitude of control parameters. It is difficult to predict a priori what surface finish will be achieved when certain values are set for these parameters. The objective of this work is to compare the models generated by decision tree algorithms (C4.5, random forest, and random tree) and to analyze which makes the best prediction of the surface roughness in polyethylene terephthalate glycol (PETG) parts printed in 3D using the FDM technique. The models have been created using a dataset of 27 instances with the following attributes: layer height, extrusion temperature, print speed, print acceleration, and flow rate. In addition, a dataset has been created to evaluate the models, consisting of 15 additional instances. The models generated by the random tree algorithm achieve the best results for predicting the surface roughness in FDM parts.

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Section: Discussionmentioning

confidence: 99%

Decision Tree Methods for Predicting Surface Roughness in Fused Deposition Modeling Parts

Barrios

Romero

2019

Materials

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“…Therefore, new data analytics methods should be developed to solve this issue. To the best of our knowledge, there are few studies [68] proposed to address this issue. • Stream data processing.…”

Section: New Data Analytics Methods For Miot Datamentioning

confidence: 99%

Big data analytics for manufacturing internet of things: opportunities, challenges and enabling technologies

Dai

Wang

et al. 2019

Enterprise Information Systems

236

137

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“…For generating a set of rules that can be used to try to explain what conditions can be decisive to the missing cause, we decide to use PART [14] algorithm of WEKA which makes a set of rules from partial J48 threes, given the previously mentioned unbalance of the data a Cost Matrix was used to perform a cost-sensitive learning in order to penalize bad classification of the missing cause [15] with the class "voluntary absence" because it is easy to see that if any classification algorithm decided to assign the value of "voluntary absence" to all records, just by the distribution of the data it would get a 63% of correctly classified instances.…”

Section: Patterns Extractionmentioning

confidence: 99%

Computational Model to Support the Detection of Profiles of Missing Person in Colombia.

Agudelo

Herrera‐Viedma

Gaona-García

2021

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In the world and some countries like Colombia, the number of missing person is a phenome very worrying and growing, every year, thousands of people are reported missing all over the world, the fact that this keeps happening might indicate that there are still analyses that have not been done and tools that have not been considered in order to find patterns in the information of missing person. The present article presents a study of the way informatics and computational tools can be used to help find missing person and what patterns can be found in missing person datasets using as a study case open data about missing person in Colombia in 2017. The goal of this study is to review how computational tools like data mining and image analysis can be used to help find missing person and draw patterns in the available information about missing person. For this, first it will be review of the state of art of image analysis in real world applications was made in order to explore the possibilities when studying the photos of missing person, then a data mining process with data of missing person in Colombia was conducted to produce a set of decision rules that can explain the cause of the disappearance, as a result is generated decision rules algorithm suggest links between socioeconomic stratification, age, gender and specific locations of Colombia and the missing person reports. In conclusion, this work reviews what information about missing person is available publicly and what analysis can me made with them, showing that data mining and face recognition can be useful tools to extract patterns and identify patterns in missing person data.

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Imbalanced classification of manufacturing quality conditions using cost-sensitive decision tree ensembles

Cited by 48 publications

References 46 publications

Decision Tree Methods for Predicting Surface Roughness in Fused Deposition Modeling Parts

Decision Tree Methods for Predicting Surface Roughness in Fused Deposition Modeling Parts

Big data analytics for manufacturing internet of things: opportunities, challenges and enabling technologies

Computational Model to Support the Detection of Profiles of Missing Person in Colombia.

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