Titlebook: Intelligent Information and Database Systems; 13th Asian Conferenc Ngoc Thanh Nguyen,Suphamit Chittayasothorn,Bogdan Conference proceeding

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Demand Forecasting for Textile Products Using Statistical Analysis and Machine Learning Algorithmsoving accuracy and performance. Where all the variables that affect the productive environment of this sector under study are considered. Finally, as a result of the analysis, multilayer perceptron achieved better performance compared to conventional and machine learning algorithms. Featuring the be

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Ngoc Thanh Nguyen,Suphamit Chittayasothorn,Bogdan

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Conference proceedings 2021et, Thailand, in April 2021.*.The 67 full papers accepted for publication in these proceedings were carefully reviewed and selected from 291 submissions. The papers of the first volume are organized in the following topical sections: data mining methods and applications; machine learning methods; de

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0302-9743 ld in Phuket, Thailand, in April 2021.*.The 67 full papers accepted for publication in these proceedings were carefully reviewed and selected from 291 submissions. The papers of the first volume are organized in the following topical sections: data mining methods and applications; machine learning m

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Session Based Recommendations Using Recurrent Neural Networks - Long Short-Term Memory best performing network has been a trainer for the last year of likes on an image-based social platform and contained about 2000 classes. Our best model has resulted in recall value 0.0213 and precision value 0.0052 on twenty items.

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Clustering Count Data with Stochastic Expectation Propagationn making inference in large datasets. Experiments on both synthetic and real count data have been conducted to validate the effectiveness of the proposed algorithm in comparison to other traditional learning approaches. Results show that SEP produces comparable estimates with traditional approaches.

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Phase Prediction of Multi-principal Element Alloys Using Support Vector Machine and Bayesian Optimizdataset consisting of the experimental results of 118 MPEAs, our solution achieves the cross-validation accuracy of 90.2%. We confirm the superiority of this score over the performance of ANN statistically. On the other dataset containing 401 MPEAs, our SVM model is comparable to ANN and exhibits 70.6% cross-validation accuracy.

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Mining Partially-Ordered Episode Rules in an Event Sequences called partially-ordered episode rules, where events in a rule are partially ordered. To efficiently find all these rules in a sequence, an efficient algorithm named POERM (Partially-Ordered Episode Rule Miner) is presented. An experimental evaluation on several benchmark dataset shows that POERM has excellent performance.

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Complexes of Low Dimensional Linear Classifiers with , Marginssupport vector machines (.) method of classifiers designing. An alternative approach to designing classifiers is linked to the local maximization of the margins of the . norm. This approach allows also designing complexes of linear classifiers on the basis of small samples of multivariate vectors.