Classification Using ANN: A Review
نویسندگان
چکیده
Classification is one of the important areas of research in the field of data mining and neural network is one of the widely used techniques for classification. Present paper discusses about artificial neural network algorithm (ANN) and its variants and their use in classification. ANN has many advantages but it has some hindrances like long training time, high computational cost, and adjustment of weight. Researchers proposed different variants of it and hybridize it with evolutionary algorithm to improve its performance. Present paper discusses about ANN and its variants and their use for the classification using ANN and its variants and their performance results.
منابع مشابه
A Review of Epidemic Forecasting Using Artificial Neural Networks
Background and aims: Since accurate forecasts help inform decisions for preventive health-careintervention and epidemic control, this goal can only be achieved by making use of appropriatetechniques and methodologies. As much as forecast precision is important, methods and modelselection procedures are critical to forecast precision. This study aimed at providing an overview o...
متن کاملThe Porosity Prediction of One of Iran South Oil Field Carbonate Reservoirs Using Support Vector Regression
Porosity is considered as an important petrophysical parameter in characterizing reservoirs, calculating in-situ oil reserves, and production evaluation. Nowadays, using intelligent techniques has become a popular method for porosity estimation. Support vector machine (SVM) a new intelligent method with a great generalization potential of modeling non-linear relationships has been introduced fo...
متن کاملمقایسه مدل شبکه عصبی مصنوعی و رگرسیون پارامتری در پیشبینی بقای بیماران مبتلا به سرطان معده
Background & Objective: Using parametric models is common approach in survival analysis. In the recent years, artificial neural network (ANN) models have increasingly used in survival prediction. The aim of this study was to predict of survival rate of patients with gastric cancer by using a parametric regression and ANN models and compare these methods. Methods: We used the data of 436 gast...
متن کاملA Novel Classification Method using Effective Neural Network and Quantitative Magnetization Transfer Imaging of Brain White Matter in Relapsing Remitting Multiple Sclerosis
Background: Quantitative Magnetization Transfer Imaging (QMTI) is often used to quantify the myelin content in multiple sclerosis (MS) lesions and normal appearing brain tissues. Also, automated classifiers such as artificial neural networks (ANNs) can significantly improve the identification and classification processes of MS clinical datasets.Objective: We classified patients with relapsing-r...
متن کاملForecasting GDP Growth Using ANN Model with Genetic Algorithm
Applying nonlinear models to estimation and forecasting economic models are now becoming more common, thanks to advances in computing technology. Artificial Neural Networks (ANN) models, which are nonlinear local optimizer models, have proven successful in forecasting economic variables. Most ANN models applied in Economics use the gradient descent method as their learning algorithm. However, t...
متن کامل