Improvement of Pre-processing Capacity of Support Vector Clustering using Neural Network Kernel Function for Stream Data Classification
2014
processing of data before generation of pattern or classification is major steps. In the phase of pre-processing reduces the noise level of data using different technique of data mining. In current research trend support vector clustering is used for efficient data processing for noise reduction and pattern generation. Support vector clustering is new paradigm of data mining tools. It combined with supervised learning and unsupervised learning. for the success story behind support vector clustering technique is kernel function. The better selection of kernel function produces better result in terms of noise reduction and classification. In this paper proposed an improved support vector clustering method using neural network kernel function for stream data classification. The neural network function work as data optimizer and data selector in support vector clustering.
Keywords:
- Correlation clustering
- Data mining
- Data stream clustering
- Cluster analysis
- Kernel method
- CURE data clustering algorithm
- Least squares support vector machine
- Machine learning
- Canopy clustering algorithm
- Pattern recognition
- Artificial intelligence
- Radial basis function kernel
- Computer science
- Relevance vector machine
- Clustering high-dimensional data
- Correction
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