Nearest prototype classifier designs: An experimental study
نویسندگان
چکیده
منابع مشابه
Nearest prototype classifier designs: An experimental study
We compare eleven methods for finding prototypes upon which to base the nearest Ž prototype classifier. Four methods for prototype selection are discussed: Wilson Hart a . condensation error-editing method , and three types of combinatorial search random search, genetic algorithm, and tabu search. Seven methods for prototype extraction are discussed: unsupervised vector quantization, supervised...
متن کاملFuzzy Nearest Prototype Classifier Applied to Speaker Identification
In a vector quantisation (VQ) based speaker identification system, a speaker model is created for each speaker from the training speech data by using the k-means clustering algorithm. For an unknown utterance analysed into a sequence of vectors, the nearest prototype classifier is used to identify speaker. To achieve the higher speaker identification accuracy, a fuzzy approach is proposed in th...
متن کاملOptimized distance metrics for differential evolution based nearest prototype classifier
In this article, we introduce a differential evolution based classifier with extension for selecting automatically the applied distance measure from a predefined pool of alternative distances measures to suit optimally for classifying the particular data set at hand. The proposed method extends the earlier differential evolution based nearest prototype classifier by extending the optimization p...
متن کاملSoft nearest prototype classification
We propose a new method for the construction of nearest prototype classifiers which is based on a Gaussian mixture ansatz and which can be interpreted as an annealed version of learning vector quantization (LVQ). The algorithm performs a gradient descent on a cost-function minimizing the classification error on the training set. We investigate the properties of the algorithm and assess its perf...
متن کاملNearest Cluster Classifier
In this paper, a new classification method that uses a clustering method to reduce the train set of K-Nearest Neighbor (KNN) classifier and also in order to enhance its performance is proposed. The proposed method is called Nearest Cluster Classifier (NCC). Inspiring the traditional K-NN algorithm, the main idea is to classify a test sample according to the tag of its nearest neighbor. First, t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Intelligent Systems
سال: 2001
ISSN: 0884-8173,1098-111X
DOI: 10.1002/int.1068