Acceleration of Binning Nearest Neighbour Methods
نویسندگان
چکیده
A new solution method to the Nearest Neighbour Problem is presented. The method is based upon the triangle inequality and works well for small point sets, where traditional solutions are particularly ineffective. Its performance is characterized experimentally and compared with k-d tree and Elias approaches. A hybrid approach is proposed wherein the triangle inequality method is applied to the k-d tree and Elias bin sets. The hybridization is shown to accelerate the k-d tree for large point sets, resulting in 20% improvement in time performance. The space efficiencies for both the k-d tree and Elias methods also improve under the hybrid scheme.
منابع مشابه
Acceleration of Binning Nearest Neighbor Methods
A new solution method to the Nearest Neighbour Problem is presented. The method is based upon the triangle inequality and works well for small point sets, where traditional solutions are particularly ineffective. Its performance is characterized experimentally and compared with k-d tree and Elias approaches. A hybrid approach is proposed wherein the triangle inequality method is applied to the ...
متن کاملOn the construction of complete and partial nearest neighbour balanced designs
In this paper, methods for constructing two dimensional nearest neighbour balanced (NNB) designs are considered. The methods given by Afsarinejad and Seeger (1988) are extended to give a new family of nearest neighbour balanced designs. Both nearest neighbour balanced designs with and without borders are constructed. A method of construction of a class of partial nearest neighbour balanced (PNN...
متن کاملLove Thy Neighbour: Automatic Animal Behavioural Classification of Acceleration Data Using the K-Nearest Neighbour Algorithm
Researchers hoping to elucidate the behaviour of species that aren't readily observed are able to do so using biotelemetry methods. Accelerometers in particular are proving particularly effective and have been used on terrestrial, aquatic and volant species with success. In the past, behavioural modes were detected in accelerometer data through manual inspection, but with developments in techno...
متن کاملAn efficient weighted nearest neighbour classifier using vertical data representation
The k-nearest neighbour (KNN) technique is a simple yet effective method for classification. In this paper, we propose an efficient weighted nearest neighbour classification algorithm, called PINE, using vertical data representation. A metric called HOBBit is used as the distance metric. The PINE algorithm applies a Gaussian podium function to set weights to different neighbours. We compare PIN...
متن کاملExtensions of the k Nearest Neighbour Methods for Classification Problems
The k Nearest Neighbour (kNN) method is a widely used technique which has found several applications in clustering and classification. In this paper, we focus on classification problems and we propose modifications of the nearest neighbour method that exploit information from the structure of a dataset. The results of our experiments using datasets from the UCI repository demonstrate that the c...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2000