Application of Machine Learning in Clustering Maize Producing Regions in Indonesiadoi:10.18495/comengapp.v13i2.455EliyaniDwiasnati, SaruniArif, Sutan MohammadAvrizal, RezaFatimah, NonaComputer Engineering & Applications Journal
Constructing a good graph to represent data structures is critical for many important machine learning tasks such as clustering and classification. Recently, a nonparameteric graph construction method called L1-graph is proposed with claimed advantages on sparsity, robustness to data noise and datum-ada...
Accordingly, the intention was to be able to carry out the analysis regularly and frequently in different collaborative environments. One of the two approaches classifies students according to their collaboration using unsupervised machine learning techniques, clustering, while the other approach constructs ...
This paper presents a new Spectral clustering analysis algorithm based on the unsupervised learning. Spectral clustering algorithm has its own unique advantage. For example, it can be clustered in any irregular shape of the sample space, but also be obtained the optimal solution in the global. The...
Quick and accurate medical diagnoses are crucial for the successful treatment of diseases. Using machine learning algorithms and based on laboratory blood test results, we have built two models to predict a haematologic disease. One predictive model used
It uses machine learning techniques and tools in determining patterns and trends to gain actionable insights. This paper selected a popular food brand to evaluate a given stream of customer comments on Twitter. Several metrics in classification and clustering of data were used for analysis. A ...
Next, the proposed clustering method is used to construct the premises of an IF-THEN rule-based classifier. The conclusions of these rules are obtained by minimization of a criterion function with various approximations of a misclassification error (e.g., based on the quadratic, the linear, the...
Therefore, we believe that a new theory and methodology based on clustering techniques, in combination with proxy models, must be developed to reduce computational costs and reliably solve real-world sequential decision-making problems. Author contributions Amine wrote the paper and contributed to ...
i.e.Pearsonsimilarityandclusteringalgorithms,theapplicationofmachinelearningtechniquessuchasLDA,CNNandSVMtorecommendationhasbeenanewareaandnotsystematicallystudiedyet.TopicmodelssuchasLDAcouldallowustolearnthelatentsubtopicsinreviewtexts,whichthencanbeusedinpersonalizedrecommendation.DeepCNNcouldbeusedtoextracttheunderlying...
et al. Contribution ratio and distribution patterns of multiple oil sources in the Yanchang Formation of the Ordos Basin: A study utilizing machine learning and interpretability techniques | [鄂尔多斯盆地延长组多油源贡献比例与分布规律: 基于机器学习与可解释性研究]. Earth Science Frontiers, 2024, 31(...