choroid
发表于 2025-3-28 18:05:14
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subacute
发表于 2025-3-28 21:17:17
Clustering Large Dynamic Datasets Using Exemplar Pointsll as the trend and type of change occuring in the data. The processing is done in an incremental point by point fashion and combines both data prediction and past history analysis to classify the unlabeled data. We present the results obtained using several datasets and compare the performance with the well known clustering algorithm CURE.
Chronological
发表于 2025-3-29 00:53:21
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/m/image/620461.jpg
Basal-Ganglia
发表于 2025-3-29 06:09:38
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雪上轻舟飞过
发表于 2025-3-29 07:35:28
978-3-540-26923-6Springer-Verlag Berlin Heidelberg 2005
groggy
发表于 2025-3-29 12:58:56
Machine Learning and Data Mining in Pattern Recognition978-3-540-31891-0Series ISSN 0302-9743 Series E-ISSN 1611-3349
过份
发表于 2025-3-29 16:48:57
Understanding Patterns with Different Subspace Classification a visualized result so the user is provided with an insight into the data with respect to discrimination for an easy interpretation. Additionally, it outperforms Decision trees in a lot of situations and is robust against outliers and missing values.
Affable
发表于 2025-3-29 22:03:46
Parameter Inference of Cost-Sensitive Boosting Algorithmssed on F-measure. Our experimental results show that one of our proposed cost-sensitive AdaBoost algorithms is superior in achieving the best identification ability on the small class among all reported cost-sensitive boosting algorithms.
mechanical
发表于 2025-3-30 02:05:52
Principles of Multi-kernel Data Miningpecific kernel function as a specific inner product. The main requirement here is to avoid discrete selection in eliminating redundant kernels with the purpose of achieving acceptable computational complexity of the fusion algorithm.
委屈
发表于 2025-3-30 06:22:57
Determining Regularization Parameters for Derivative Free Neural Learningmentioned problem is the problem of large weight values for the synaptic connections of the network. Large synaptic weight values often lead to the problem of paralysis and convergence problem especially when a hybrid model is used for fine tuning the learning task. In this paper we study and analys