In this paper comparison is done between k-nearest neighbor and naïve basin classifier based on the subset of features. Sequential feature selection method is used to establish the subsets. Four categories of subsets are used like life and medical transcripts, arts and humanities transcripts, social science transcripts, physical science transcripts to show the experimental results to classify d...

Because of the massive increase in the size of the data it becomes troublesome to perform effective analysis using the current traditional techniques. Big data put forward a lot of challenges due to its several characteristics like volume, velocity, variety, variability, value and complexity. Today there is not only a necessity for efficient data mining techniques to process large volume of dat...

This paper proposes a new classification method termed Rectified Nearest Feature Line Segment (RNFLS). It overcomes the drawbacks of the original Nearest Feature Line (NFL) classifier and possesses a novel property that centralizes the probability density of the initial sample distribution, which significantly enhances the classification ability. Another remarkable merit is that RNFLS is applic...

In many applications, different kinds of moments have been utilized to classify images and object shapes. Moments are important features used in recognition of different types of images. In this paper, three kinds of moments: Geometrical, Zernike and Legendre Moments have been evaluated for classifying 3D object images using Nearest Neighbor classifier. Experiments are conducted using ETH-80 da...

An investigation has been conducted on two well known similarity-based learning approaches to text categorization: the k-nearest neighbor (k-NN) classifier and the Rocchio classifier. After identifying the weakness and strength of each technique, a new classifier called the kNN model-based classifier (kNNModel) has been proposed. It combines the strength of both k-NN and Rocchio. A text categor...

This paper describes a technique for the recognition of off-line handwritten Arabic (Indian) numerals using Radon-Fourier-based features. A two stage classification scheme is used. The Nearest Mean (NMC), K-Nearest Neighbor (K-NNC), and Hidden Markov Models (HMMC) Classifiers are used in the first stage and a Structural Classifier (SC) is used in the second stage. A database of 44 writers with ...

Many studies have been carried out to find an appropriate method to classify the remote sensing data.Traditional classification approaches are all pixel-based, and do not utilize the spatial information within an object which is an important source of information to image classification. Instead of pixels, pixel groups and object oriented techniques offer the suitable analysed to classify satel...

This paper considers how to conduct k-nearest neighbor classification in the following scenario: multiple parties, each having a private data set, want to collaboratively build a k-nearest neighbor classifier without disclosing their private data to each other or any other parties. Specifically, the data are vertically partitioned in that all parties have data about all the instances involved, ...