Higher Education, or tertiary education, is the final stage which optional in formal education. It usually organized form of a university, academy, seminary, high school, institute. Every institution needs qualified and professional educators because they have an important role process implementing Tri Dharma Education. Recruitment for teaching staff has several stages standardization assessmen...

The recognition of handwritten numeral is an important area of research for its applications in post office, banks and other organizations. This paper presents automatic recognition of handwritten Kannada numerals based on structural features. Five different types of features, namely, profile based 10-segment string, water reservoir; vertical and horizontal strokes, end points and average bound...

A brain computer interface (BCI) enables direct communication between a brain and a computer translating brain activity into computer commands usi ng preprocessing, feature extraction and classification operations. Feature extraction is crucial as it has a substantial effect on the classification accuracy and speed. While fractal dimension has been successfully used in various domains to charac...

In this paper, we propose novel methods to find the best relevant feature subset using fuzzy rough set-based attribute subset selection with biologically inspired algorithm search such as ant colony and particle swarm optimization and the principles of an evolutionary process. We then propose a hybrid fuzzy rough with K-nearest neighbor (KNN)-based classifier (FRNN) to classify the patterns in ...

Amphiphilic pseudo-amino acid composition (Am-Pse-AAC) with extra sequence-order information is a useful feature for representing enzymes. This study first utilizes the k-nearest neighbor (k-NN) rule to analyze the distribution of enzymes in the Am-Pse-AAC feature space. This analysis indicates the distributions of multiple classes of enzymes are highly overlapped. To cope with the overlap prob...

Given a point query Q in multi-dimensional space, K-Nearest Neighbor (KNN) queries return the K closest answers in the database with respect to Q. In this scenario, it is possible that a majority of the answers may be very similar to one or more of the other answers, especially when the data has clusters. For a variety of applications, such homogeneous result sets may not add value to the user....

Data Mining has great scope in the field of medicine. In this article we introduced one new fuzzy approach for prediction of hepatitis disease. Many researchers have proposed the use of K-nearest neighbor (KNN) for diabetes disease prediction. Some have proposed a different approach by using K-means clustering for reprocessing and then using KNN for classification. In our approach Naive Bayes c...

Many sophisticated classification algorithms have been proposed. However, there is no clear methodology of comparing the results among different methods. According to our experiments on the popular datasets, k-NN with properly tuned parameters performs on average best. Tuning the parametres include the proper k, proper distance measure and proper weighing functions. k-NN has a zero training tim...

A novel approach for k-nearest neighbor (k-NN) searching with Euclidean metric is described. It is well known that many sophisticated algorithms cannot beat the brute-force algorithm when the dimensionality is high. In this study, a probably correct approach, in which the correct set of k-nearest neighbors is obtained in high probability, is proposed for greatly reducing the searching time. We ...