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Titlebook: Machine Learning and Data Mining in Pattern Recognition; 13th International C Petra Perner Conference proceedings 2017 Springer Internation

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31#
發(fā)表于 2025-3-26 21:33:47 | 只看該作者
Qualitative and Descriptive Topic Extraction from Movie Reviews Using LDA,ion from text reviews using Latent Dirichlet Allocation (LDA) based topic models. Our models extract distinct qualitative and descriptive topics by combining text reviews and movie ratings in a joint probabilistic model. We evaluate our models on an IMDB dataset and illustrate its performance through comparison of topics.
32#
發(fā)表于 2025-3-27 01:38:14 | 只看該作者
33#
發(fā)表于 2025-3-27 07:48:34 | 只看該作者
34#
發(fā)表于 2025-3-27 09:43:14 | 只看該作者
0302-9743 ing to specific data mining methods for the different multi-media data types such as image mining, text mining, video mining, and Web mining..978-3-319-62415-0978-3-319-62416-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
35#
發(fā)表于 2025-3-27 17:40:31 | 只看該作者
0302-9743 Data Mining in Pattern Recognition, MLDM 2017, held in New York, NY, USA in July/August 2017.The 31 full papers presented in this book were carefully reviewed and selected from 150 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern min
36#
發(fā)表于 2025-3-27 20:30:19 | 只看該作者
37#
發(fā)表于 2025-3-27 23:16:36 | 只看該作者
Machine Learning-as-a-Service and Its Application to Medical Informatics,ontribution, we provide a comparison of several state-of-the-art Machine Learning-as-a-Service platforms along with their capabilities in medical informatics. In addition, we performed several analyses to examine the qualitative and quantitative attributes of two Machine Learning-as-a-Service environments namely “BigML” and “Algorithmia”.
38#
發(fā)表于 2025-3-28 04:22:25 | 只看該作者
Prediction of Insurance Claim Severity Loss Using Regression Models, the final loss value was also predicted with an error of 0.440 using FFNN regression model. We also demonstrate the use of lasso regularization to avoid over-fitting for some of the regression models.
39#
發(fā)表于 2025-3-28 10:19:38 | 只看該作者
40#
發(fā)表于 2025-3-28 12:07:33 | 只看該作者
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