regression techniques
Evaluation of linear regression techniques for atmospheric applications: the importance of appropriate weighting
... Linear regression techniques are widely used in at- mospheric science, but they are often improperly applied due to lack of consideration or inappropriate handling of mea- surement ...gression ...
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Comment Prediction in Facebook Pages using Regression Techniques
... This paper examines the Decision Tree, KNN, linear Regression and Random Forest results and concluding that KNN gives expected results compared to other Algorithms in comment volume prediction model. Moreover, ...
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Econometric applications of high breakdown robust regression techniques
... robust regression estimators (least median squares (LMS), least trimmed squares (LTS), and variants) which behave reasonably even in the presence of a large number of ...breakdown techniques are discussed ...
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Intelligent feature selection for neural regression : techniques and applications
... these techniques, ANNs are often referred to as ‘black box’ models as there is generally no interactive activity with an ANN apart from feeding it with the available ...data regression and ...
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Performance Evaluation of Regression Techniques for Effort Estimation
... Software effort estimation assesses the quantity of work required to develop a software project. It is a well known fact that the software industry is unable to give proper an estimate of effort, time and development ...
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Efficient Classification And Regression Techniques To Predict Crop Yield
... mining techniques to analyze available data set, mining useful patterns and obtaining predictions using generalized linear model, deep learning, decision tree, random forest, and gradient boosted trees and support ...
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Bayesian variants of some classical semiparametric regression techniques
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Using Stepwise Regression Techniques to Shortlist the Number of Antecedents of Employee Absenteeism
... linear regression including all the variables that are found in the stepwise method, this variable (the interaction of tenure and function) does not appear to be ...
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Estimating physiological tolerances – a comparison of traditional approaches to nonlinear regression techniques
... approach coupled with simple differential calculus. We then evaluate the performance of this new method relative to the most widely used approach to date, BSR, across real-world data and explore a broader parameter space ...
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Impact Of Audit Committee Membership Gender Diversity On Quality Of Financial Reporting Of Deposits Money Banks in Nigeria
... Multivariate Regression Techniques (Fixed and random test regression) to establish that the independent variables (Gender Diversity) on one hand explains a proportion in the dependent variable ...
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Productivity modeling of precast concrete installation using multiple regression analysis
... different regression models for preparation, lift, and fixing ...stepwise regression techniques were utilized in model developments and the significant factors to build the models were identified ...
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Ten Spatial Problems with myGeoffice© for Teaching Purposes
... Weighted Regression (GWR) is one of several spatial regression techniques that provides a local model of the variable the researcher are trying to understand/predict (dependent variable) by fitting a ...
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Integrative regression network for genomic association study
... integrative regression network that identifies genomic associations on multiple high-dimensional genomic profiles by taking into account the associations between as well as within ...high-dimensional ...
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Jackknife And Bootstrap Techniques In The Estimation of regression Parameters
... bootstrap regression techniques are to require little sample than OLS procedure and its theoretical accomplishments is often much better yet this is not warranted ...bootstrap regression technique ...
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A Survey on Regression Test Selection Techniques on Aspect Oriented Programming
... Rothermal and harrold proposes an approach which is based on graph traversal algorithm. In their approach aspect oriented features (such as point cuts, join points, aspects, advice [14]) are added into object oreinted ...
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Analysis of Multiple Classification Algorithms using Real Time Twitter Data
... Clustering Regression technique can be fitting for predication. Regression analysis can be used to create (procedure) model the relationship between one or more independent variables and dependent ...
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An Overview of Classification Algorithms and Ensemble Methods in Personal Credit Scoring
... Linear regression is an essential component of any data analysis, deals with describing the relationship between a target feature and one or more independent ...Linear regression is used in credit scoring ...
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Diabetic retinopathy risk prediction for fundus examination using sparse learning: a cross-sectional study
... The LASSO, the most well-known sparse learning technique, predicted DR most efficiently. ROC analysis supported that the LASSO model had a statistically sig- nificant improvement in predicting DR. This finding is ...
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Regression Estimation Modelling Techniques on Static Solar Photovoltaic Module
... statistical techniques applied to various research ...[9-10]. Regression analysis tries to fit a model to one dependent variable based on one or more independent ...common regression models is the ...
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Application of Budgeting Techniques in Fiscal Institutions in Nigeria
... research work revealed that budgeting has helped to control the differences between budgeted and actual revenue, recurrent expenditure and capital expenditure to ensure better economic performance. The data used in this ...
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