A nonparametric statistical tool based on kernel function estimation is developed for spatial rainfall characterization. In this method, observations closer to the point of estimate are weighted higher using kernel function with a prescribed bandwidth. The kernel bandwidth is local and it extends only to the K Nearest Neighbor, KNN, observation. An optimal value for KNN is selected by cross val...

The solid-state method was used to synthesize single phase potassium-sodium niobate (KNN) co-doped with the La3+-Mn4+ and Eu3+-Fe3+ ion pairs. Structural determination of all studied solid solutions was accomplished by XRD and Rietveld refinement method. Electron paramagnetic resonance (EPR) studies were performed to determine the oxidation state of paramagnetic centers. Optical spectroscopy me...

In this experimentation project, we introduce the Neighbourhood Component Analysis (NCA), a classification method combining k-nearest neighbour (KNN) and learned distance metric, originally proposed by Goldberger et al. in 2004. With an implementation in the R environment, we perform experiments on several datasets. Results of our experiments suggest that with the learned distance metric, KNN c...

We investigated how Half-Against-Half Support Vector Machine (HAH-SVM) and Half-Against-Half kNearest Neighbour (HAH-KNN) methods succeed in the classification of the benthic macroinvertebrate images. Automated taxa identification of benthic macroinvertebrates is a slightly researched area and in this paper HAH-KNN was for the first time applied to this application area. The main problem, when ...

Our final solution (RMSE=0.8712) consists of blending 107 individual results. Since many of these results are close variants, we first describe the main approaches behind them. Then, we will move to describing each individual result. The core components of the solution are published in our ICDM'2007 paper [1] (or, KDD-Cup'2007 paper [2]), and also in the earlier KDD'2007 paper [3]. We assume th...