منابع مشابه
Drought Monitoring and Prediction using K-Nearest Neighbor Algorithm
Drought is a climate phenomenon which might occur in any climate condition and all regions on the earth. Effective drought management depends on the application of appropriate drought indices. Drought indices are variables which are used to detect and characterize drought conditions. In this study, it was tried to predict drought occurrence, based on the standard precipitation index (SPI), usin...
متن کاملFast Approximate Nearest-Neighbor Search with k-Nearest Neighbor Graph
We introduce a new nearest neighbor search algorithm. The algorithm builds a nearest neighbor graph in an offline phase and when queried with a new point, performs hill-climbing starting from a randomly sampled node of the graph. We provide theoretical guarantees for the accuracy and the computational complexity and empirically show the effectiveness of this algorithm.
متن کاملUnsupervised K-Nearest Neighbor Regression
In many scientific disciplines structures in highdimensional data have to be found, e.g., in stellar spectra, in genome data, or in face recognition tasks. In this work we present a novel approach to non-linear dimensionality reduction. It is based on fitting K-nearest neighbor regression to the unsupervised regression framework for learning of low-dimensional manifolds. Similar to related appr...
متن کاملNeighbor-weighted K-nearest neighbor for unbalanced text corpus
Text categorization or classification is the automated assigning of text documents to pre-defined classes based on their contents. Many of classification algorithms usually assume that the training examples are evenly distributed among different classes. However, unbalanced data sets often appear in many practical applications. In order to deal with uneven text sets, we propose the neighbor-wei...
متن کاملEvolving edited k-Nearest Neighbor Classifiers
The k-nearest neighbor method is a classifier based on the evaluation of the distances to each pattern in the training set. The edited version of this method consists of the application of this classifier with a subset of the complete training set in which some of the training patterns are excluded, in order to reduce the classification error rate. In recent works, genetic algorithms have been ...
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ژورنال
عنوان ژورنال: Scholarpedia
سال: 2009
ISSN: 1941-6016
DOI: 10.4249/scholarpedia.1883