Currently, Nearest-Neighbor approaches (NN) have been applied to large scale real world image data mining. However, the following three disadvantages prevent them from wider application compared to other machine learning methods: (i) the performance is inferior on small datasets; (ii) the performance will degrade for data with high dimensions; (iii) they are heavily dependent on the chosen feat...

Spectral clustering is a method of subspace clustering which is suitable for the data of any shape and converges to global optimal solution. By combining concepts of shared nearest neighbors and geodesic distance with spectral clustering, a self-adaptive spectral clustering based on geodesic distance and shared nearest neighbors was proposed. Experiments show that the improved spectral clusteri...

Several analyses of self-segregation properties of reaction-diffusion systems in low dimensions have been based on a simplified model in which an initially uniform concentration of point particles is depleted by reaction with an immobilized trap. A measure of selfsegregation in this system is the distance of the trap from the nearest untrapped particle. In one dimension the average of this dist...

This paper we proposes an extended geodesic distance for head pose estimation. In ISOMAP, two approaches are applied for neighborhood construction, called k-neighbor and -neighbor. For the kneighbor, the number of the neighbors is a const k. For the other one, all the distances between the neighbors is less than . Either the k-neighbor or the -neighbor neglects the difference of each point. Thi...

A growing number of studies have shown that adequate spatial access to healthy foods leads to increased fresh produce consumption and reduced risk of chronic diseases. Annual dynamics of spatial access to 1,539 vendors of fresh produce (including farmers markets and roadside farm stands) are analyzed in Massachusetts. Travel distance to the nearest fresh produce vendor was calculated for each c...

In this paper, we ask “Can proximity to towns reduces poverty in rural areas?” For this study we have mapped all the villages in Orissa. The study is based on small area poverty estimation methodology as well as the secondary data covering 47,395 villages and 109 towns. Our main findings are (i) there is a relationship between the distance to nearest town and rural poverty and (ii) poverty leve...

We propose a new approach for outlier detection, based on a new ranking measure that focuses on the question of whether a point is “important” for its nearest neighbors; using our notations low cumulative rank implies the point is central. For instance, a point centrally located in a cluster has relatively low cumulative sum of ranks because it is among the nearest neighbors of its own nearest ...

Instead of using the same ensemble for all data instances, recent studies have focused on dynamic ensembles in which a new ensemble is chosen from a pool of classifiers for each new data instance. Classifiers agreement in the region where a new data instance resides in has been considered as a major factor in dynamic ensembles. We postulate that the classifiers chosen for a dynamic ensemble sho...

The i-vector model is widely used by the state-of-the-art speaker recognition system. We proposed a new Mahalanobis metric scoring learned from weighted pairwise constraints (WPCML), which use the different weights for the empirical error of the similar and dissimilar pairs. In the new i-vector space described by the metric, the distance between the same speaker’s i-vectors is small, while that...