نتایج جستجو برای: feature reduction

تعداد نتایج: 713021  

Journal: :iranian journal of diabetes and obesity 0
razieh sheikhpour school of electrical and computer engineering, yazd university, yazd, iran. mehdi agha sarram school of electrical and computer engineering, yazd university, yazd, iran.

objective: diabetes is one of the most common metabolic diseases. earlier diagnosis of diabetes and treatment of hyperglycemia and related metabolic abnormalities is of vital importance. diagnosis of diabetes via proper interpretation of the diabetes data is an important classification problem. classification systems help the clinicians to predict the risk factors that cause the diabetes or pre...

Journal: :international journal of bio-inorganic hybrid nanomaterials 0

in this work, we report synthesis of silver nanoplates by a simple reduction process of silver nitrate in the presence of polyvinyl alcohol (pva) and n,n'-dimethyl formamide (dmf). the characterization of the samples were carried out using x-ray diffraction (xrd), transmission-electron microscopy (tem) and uv-vis spectroscopy. absorption spectra of the nanoplates in comparison with that of...

Journal: :iranian journal of chemistry and chemical engineering (ijcce) 2010
reza shamsaee mahmood fathy ali masoudi-nejad

the dna microarray is an important technique that allows researchers to analyze many gene expression data in parallel. although the data can be more significant if they come out of separate experiments, one of the most challenging phases in the microarray context is the integration of separate expression level datasets that have gathered through different techniques. in this paper, we present a...

Journal: :journal of ai and data mining 2015
maryam imani hassan ghassemian

when the number of training samples is limited, feature reduction plays an important role in classification of hyperspectral images. in this paper, we propose a supervised feature extraction method based on discriminant analysis (da) which uses the first principal component (pc1) to weight the scatter matrices. the proposed method, called da-pc1, copes with the small sample size problem and has...

Journal: :international journal of smart electrical engineering 2012
sepideh araban fardad farokhi kaveh kangarloo

detecting faces in cluttered backgrounds and real world has remained as an unsolved problem yet. in this paper, by using composition of some kind of independent features and one of the most common appearance based approaches, and multilayered perceptron (mlp) neural networks, not only some questions have been answered, but also the designed system achieved better performance rather than the pre...

Dimensionality reduction methods transform or select a low dimensional feature space to efficiently represent the original high dimensional feature space of data. Feature reduction techniques are an important step in many pattern recognition problems in different fields especially in analyzing of high dimensional data. Hyperspectral images are acquired by remote sensors and human face images ar...

Journal: :journal of advances in computer research 2013
vahid majidnezhad igor kheidorov

acoustic analysis is a proper method in vocal fold pathology diagnosis so that itcan complement and in some cases replace the other invasive, based on direct vocalfold observation, methods. there are different approaches and algorithms for vocalfold pathology diagnosis. these algorithms usually have three stages which arefeature extraction, feature reduction and classification. in this paper in...

Journal: :Complex & Intelligent Systems 2022

Abstract As basic research, it has also received increasing attention from people that the “curse of dimensionality” will lead to increase cost data storage and computing; influences efficiency accuracy dealing with problems. Feature dimensionality reduction as a key link in process pattern recognition become one hot difficulty spot field recognition, machine learning mining. It is most challen...

2015
Dmitry Storcheus Afshin Rostamizadeh Sanjiv Kumar

The problem of extracting features from given input data is of critical importance for the successful application of machine learning. Feature extraction, as usually understood, seeks an optimal transformation from input data into a (typically real-valued) feature vector that can be used as an input for a learning algorithm. Over time, this problem has been attacked using a growing number of di...

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