This paper describes a machine learning method, called Regression by Feature Projections (RFP), for predicting a real-valued target feature. In RFP training is based on simply storing the projections of the training instances on each feature separately. Prediction is computed through two approximation procedures. The first approximation process is to find the individual predictions of features ...

Many fundamental problems for approximate polynomials can be reformulated as structured linear approximation problems. Problems such as finding polynomials with a GCD which are nearest to given relatively prime polynomials, finding the nearest Ore polynomials with a non-trivial GCRD, finding the nearest polynomial which functionally decomposes, and finding the nearest multivariate polynomial wh...

In the present paper, we introduce a new type of Bernstein-Durrmeyer operators preserving linear functions in movable interval. The approximation rate for continuous and Voronovskaja?s asymptotic estimate are obtained.

Accurately representing synonymy using distributional similarity requires large volumes of data to reliably represent infrequent words. However, the naı̈ve nearest-neighbour approach to compare context vectors extracted from large corpora scales poorly. The Spatial Approximation Sample Hierarchy (SASH) is a data-structure for performing approximate nearest-neighbour queries, and has been previou...

Many pattern recognition tasks make use of the k nearest neighbour (k–NN) technique. In this paper we are interested on fast k– NN search algorithms that can work in any metric space i.e. they are not restricted to Euclidean–like distance functions. Only symmetric and triangle inequality properties are required for the distance. A large set of such fast k–NN search algorithms have been develope...

The interval set is a special set, which describes uncertainty of an uncertain concept or set Z with its two crisp boundaries named upper-bound set and lower-bound set. In this paper, the concept of similarity degree between two interval sets is defined at first, and then the similarity degrees between an interval set and its two approximations (i.e., upper approximation set (R)(Z) and lower ap...