KNN is one of the most popular classification methods, but it often fails to work well with inappropriate choice of distance metric or due to the presence of numerous class-irrelevant features. Linear feature transformation methods have been widely applied to extract class-relevant information to improve kNN classification, which is very limited in many applications. Kernels have been used to l...

The k-nearest neighbor (kNN) is one of the simplest classification methods used in machine learning. Since the main component of kNN is a distance metric, kernelization of kNN is possible. In this paper kNN and semi-supervised kNN algorithms are empirically compared on two data sets (the USPS data set and a subset of the Reuters-21578 text categorization corpus). We use a soft version of the kN...

Optoelectronic modules have a wide range of applications in the field wireless communication. However, function mobile localization has not been realized optoelectronic modules. In this paper, an indoor positioning algorithm, which was based on frequency modulation (FM) signals, Firstly, FM monitoring receiver DB4004 used to collect signals; Secondly, signals were preprocessed and analyzed buil...

In this paper we describe our approach and task for the PAN 2013 Author Identification. Best thing for an intelligent application is a large corpus, but when it is small, it would be helpful to extract many features from dataset and study on them. So, we extract many features from documents like: word bag, stop word bag, punctuation bag, part of speech (POS) bag and etc. It is so important that...

<span id="docs-internal-guid-b63d466d-7fff-f94f-7540-9cb92d7bb505"><span>The evolution of classification opinion mining and user review analysis span from decades reaching into ubiquitous computing in efforts such as movie analysis. The performance linear non-linear models are discussed to classify the positive negative reviews data sets. effectiveness algorithms tested compared in-...

[1] A. Levin, D. Lischinski, and Y. Weiss. A closed-form solution to natural image matting. IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI), 30(2):0162–8828, 2008. [2] Q. Chen, D. Li, and C.-K. Tang. Knn matting. In Proc. of Computer Vision and Pattern Recognition (CVPR), 2012. [3] E. Shahrian and D. Rajan. Weighted color and texture sample selection for image matti ng. In Proc. of Computer Vis...

Indoor localisation is the state-of-the-art to identify and observe a moving human or object inside a building. Location Fingerprinting is a cost-effective software-based solution utilising the built-in wireless signal of the building to estimate the most probable position of a real-time signal data. In this paper, we apply the Conformal Prediction (CP) algorithm to further enhance the Fingerpr...

This paper proposed a new weighted KNN data filling algorithm based on grey correlation analysis (GBWKNN) by researching the nearest neighbor of missing data filling method. It is aimed at that missing data is not sensitive to noise data and combined with grey system theory and the advantage of the K nearest neighbor algorithm. The experimental results on six UCI data sets showed that its filli...

Chloroplasts are organelles found in cells of green plants and eukaryotic algae that conduct photosynthesis. Knowing a protein's subchloroplast location provides in-depth insights about the protein's function and the microenvironment where it interacts with other molecules. In this paper, we present BS-KNN, a bit-score weighted K-nearest neighbor method for predicting proteins' subchloroplast l...