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Get PriceIn this paper we consider high dimensional quadratic classifiers in non sparse settings Let boldmath{ x } 0 = x 01 x 0 p T be an observation vector of an individual belonging to one of the two populations
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Get PriceDownload PDF Abstract In this paper a high speed online neural network classifier based on extreme learning machines for multi label classification is proposed In multi label classification each of the input data sample belongs to one or more than one of the target labels The traditional binary and multi class classification where each sample belongs to only one target class forms the
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Get PriceThis paper presents a scalable decision tree algorithm for classifying large dataset with high processing speed which requires only one scan over the dataset and significantly reduces the IO cost and also requires one time sorting for numerical attributes which leads to a better performance in time dimension Knowledge discovery is an important tool for the intelligent business to transform
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Get PriceIn this paper we propose a high speed multi label classifier based on extreme learning machines ELM The proposed ELM based approach outperforms all existing multi label classifiers with respect to training time and testing time and other performance metrics The rest of the paper is organized as follows
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Get PriceCross validate the models To increase execution speed transpose the predictor data and specify that the observations are in columns Estimate the coefficients using SpaRSA Lower the tolerance on the gradient of the objective function to 1e 8
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