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Titlebook: Machine Learning and Data Mining in Pattern Recognition; 11th International C Petra Perner Conference proceedings 2015 Springer Internation

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樓主: 凝固
11#
發(fā)表于 2025-3-23 11:52:20 | 只看該作者
12#
發(fā)表于 2025-3-23 16:51:26 | 只看該作者
Local and Global Genetic Fuzzy Pattern Classifiersimentally evaluated on a sample of several public datasets, and performance is found to be significantly better than existing fuzzy pattern classifier methods. This is despite the simplicity of the fuzzy pattern classifier model, which makes it interesting.
13#
發(fā)表于 2025-3-23 18:39:28 | 只看該作者
14#
發(fā)表于 2025-3-24 00:12:55 | 只看該作者
Efficient Mining of High-Utility Sequential Rulesule Miner), which includes several optimizations to mine high-utility sequential rules efficiently. An extensive experimental study with four datasets shows that HUSRM is highly efficient and that its optimizations improve its execution time by up?to 25 times and its memory usage by up?to 50?%.
15#
發(fā)表于 2025-3-24 05:47:59 | 只看該作者
Classifying Grasslands and Cultivated Pastures in the Brazilian Cerrado Using Support Vector Machinerom EVI indices can aid in the classification process. The best result obtained an accuracy of 85.96?% in the study area, identifying data and attributes required to map pasture and native grassland in Cerrado.
16#
發(fā)表于 2025-3-24 08:58:34 | 只看該作者
17#
發(fā)表于 2025-3-24 14:00:11 | 只看該作者
Sentiment Analysis for Government: An Optimized ApproachItalian tweets in the context of a Public Administration event, also taking into account the size of the training set. This work uses a dataset of 1,700 Italian tweets relating to the public event of “Lecce 2019 – European Capital of Culture”.
18#
發(fā)表于 2025-3-24 18:30:13 | 只看該作者
19#
發(fā)表于 2025-3-24 19:21:11 | 只看該作者
Robust Principal Component Analysis of Data with Missing Valuess are first focused on carefully designed simulated tests where the ground truth is known and can be used to assess the accuracy of the results of the different methods. In addition, a practical application and evaluation of the methods for an educational data set is given.
20#
發(fā)表于 2025-3-25 01:17:52 | 只看該作者
MOGACAR: A Method for Filtering Interesting Classification Association Rulesg association rules when there are multiple technical and business interestingness measures; MOGACAR uses a multi-objective optimization method based on genetic algorithm for classification association rules, with the intention to find the most interesting, and still valid, itemsets and rules.
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