In this paper we evaluate an instance-based spam filter based on the SVM nearest neighbor (SVM-NN) classifier, which combines the ideas of SVM and k-nearest neighbor. To label a message the classifier first finds k nearest labeled messages, and then an SVM model is trained on these k samples and used to label the unknown sample. Here we present preliminary results of the comparison of SVM-NN wi...

Approximate nearest neighbor search is a technique which greatly reduces processing time and required amount of memory. Generally, there are the relationships of trade-off among accuracy, processing time and memory amount. Therefore, analysis on the relationships is an important task for practical application of the approximate nearest neighbor search method. In this paper, we construct a model...

The (k-)nearest neighbor searching has very high computational costs. The algorithms presented for nearest neighbor search in high dimensional spaces have have suffered from curse of dimensionality, which affects either runtime or storage requirements of the algorithms terribly. Parallelization of nearest neighbor search is a suitable solution for decreasing the workload caused by nearest neigh...

This paper explores the use of a model neural network for motor learning. Steinbuch and Taylor presented neural network designs to do nearest neighbor lookup in the early 1960s. In this paper their nearest neighbor network is augmented with a local model network, which fits a local model to a set of nearest neighbors. The network design is equivalent to local regression. This network architectu...

Batik is an Indonesian cultural heritage that should be preserved. Over time, many batik motifs have sprung up, which can lead to mutual claims between craftsmen. Therefore, it necessary create a system measure the similarity of motif. This research focused on making Content-Based Image Retrieval (CBIR) images. The dataset used in this big data authors transfer learning several pre-trained mode...