Logistic Regression (LR)
PREDICTION OF STOCK PERFORMANCE IN INDIAN STOCK MARKET USING LOGISTIC REGRESSION
... Information Logistic regression (LR), which is helpful for predicting the presence or absence of a characteristic or outcome based on values of a set of predictor variables, is a multivariate ...
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Logistic Regression Model for Prediction of Airway Reversibility Using Peak Expiratory Flow
... Logistic regression model: LR is useful for situations where researcher wants to be able to predict the presence or absence of a characteristic or outcome based on values of a set of predictor ...
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Using Logistic Regression Model to Predict the Success of Bank Telemarketing
... following table. A confusion matrix is plotted to demonstrate the match between the predicted value and the real value. In this study, successfully subscribing the time posits is regarded as interesting category called ...
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Logistic regression for circular data
... and with the improvement of the statistical software, the maximum likelihood method was used with some numerical methods to estimate the model parameters. The logistic regression model is used to analyse ...
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Logistic regression applied to natural hazards: rare event logistic regression with replications
... event logistic regression technique. Our so-called rare event logistic regression with replications builds some concepts from probabilistic theory into rare event logistic ...
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Diabetic retinopathy risk prediction for fundus examination using sparse learning: a cross-sectional study
... penalized logistic regres- sion models using the 5-fold cross validation as λ is ...penalized logistic regression including ridge, elastic net, and LASSO, the resulting coef- ficients models that we ...
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Algorithm Tuning from Comparative Analysis of Classification Algorithms
... Logistic Regression(LR): Linear regression can easily be used for classification in domains with numeric ...any regression technique, whether linear or nonlinear, for ...a ...
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A classification approach for power distribution systems fault cause identification
... methods, logistic regression (LR) and artificial neural network (ANN) applied to mine the historical outage data for power distribution fault cause classification, are ...regular LR is a para- ...
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Would credit scoring work for Islamic finance? A neural network approach
... Design/methodology/approach – A real data-set of 487 applicants are used consisting of 336 accepted credit applications and 151 rejected credit applications make to an Islamic finance house in the UK. In order to build ...
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Performance Evaluation of Machine Learning Approaches for Credit Scoring
... and Logistic Regression (LR) are the statistical techniques selected and Decision Tree (DT), Support Vector Machine (SVM), Random Forest (RF), Gradient Boosting Decision Tree (GBDT), eXtreme Gradient ...
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Characteristic Analysis of Smartphone Applications Satisfying Sustainable Popularity Condition: Case of Japanese Free Games
... 6, logistic regression (LR) and decision tree (DT) are used to establish several segmentation algorithms for identifying smartphone applications satisfying the sustainable popularity condition, based ...
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Predicting beta-turns in proteins using support vector machines with fractional polynomials
... Results: We propose an approach that combines support vector machines (SVMs) and logistic regression (LR) in a hybrid prediction method, which we call (H-SVM-LR) to predict β -turns in ...
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A Fully Bayesian Sparse Probit Model for Text Categorization
... discrete: Logistic Regression (LR) among others have been used to fit models with discrete/categorical response ...using logistic LR is that when the number of covariates is large, ...
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Multiclass analysis and prediction with network structured covariates
... of LR-HomoGraph proposed in “Logistic regression with homogeneous graphically structured predictors” section, we first construct the network structures, displayed in ...“Logistic ...
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Determinants of Cesarean Section among Primiparas: A Comparison of Classification Methods
... to LR and RF can be due to the interac- tions among the predictors and a non-linear na- ture of association between CS and the predic- ...of logistic regression and artificial neural network was ...
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Applying machine learning to predict future adherence to physical activity programs
... AUC: Area Under Curve; DiPS: Discontinuation Prediction Score; EWS: Early Warning Score; LR: Logistic Regression; METs: Metabolic Equivalents; mPED: Mobile Phone-Based Physical Activity [r] ...
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A Survey on Various Classification Techniques for Medical Image Data
... Table 1 shows, for each dataset, the estimated classification accuracy of the nine algorithms. As one can see from Table 2, the classification accuracy of the C5.0 algorithm tends to be better in five out of the nine ...
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Spatial epidemiological determinants of severe fever with thrombocytopenia syndrome in Miyazaki, Japan: a GWLR modeling study
... a logistic regression (LR) ...weighted logistic regression (GWLR) was ...the regression coefficient, resulting in erroneous conclusions about the significance of results ...the ...
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Functional Data Analysis Applied to Modeling of Severe Acute Mucositis and Dysphagia Resulting From Head and Neck Radiation Therapy.
... Functional logistic regression uses functional data to predict binary ...Functional logistic regression has recently been applied to NTCP modeling by Benadjaoud et ...squares regression ...
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Polytomous diagnosis of ovarian tumors as benign, borderline, primary invasive or metastatic: development and validation of standard and kernel-based risk prediction models
... For logistic regression models, we were careful regarding variable selection due to the small number of borderline and metastatic tumors. We did not use automated pro- cedures based on p-values to directly ...
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