ROC Curves for Continuous Data 1st Edition by Wojtek J Krzanowski, David J Hand ISBN 1439800219 9781439800218

ROC Curves for Continuous Data 1st Edition by Wojtek J Krzanowski, David J Hand – Ebook PDF Instant Download/Delivery: 1439800219, 9781439800218
Full download ROC Curves for Continuous Data 1st Edition after payment

Product details:

ISBN 10: 1439800219 
ISBN 13: 9781439800218
Author: Wojtek J Krzanowski, David J Hand

ROC Curves for Continuous Data 1st Table of contents:

Chapter 1: Introduction
1.1 Background
1.2 Classification
1.3 Classifier performance assessment
1.4 The ROC curve
1.5 Further reading
Chapter 2: Population ROC curves
2.1 Introduction
2.2 The ROC curve
2.2.1 Definition
2.2.2 General features
2.2.3 Properties of the ROC
Property 1
Property 2
Property 3
2.2.4 Continuous scores
2.3 Slope of the ROC curve and optimality results
2.3.1 Cost-weighted misclassification rates
2.3.2 The Neyman-Pearson Lemma
2.4 Summary indices of the ROC curve
2.4.1 Area under the ROC curve
2.4.2 Single points and partial areas
2.4.3 Other summary indices
2.5 The binormal model
2.6 Further reading
Chapter 3: Estimation
3.1 Introduction
3.2 Preliminaries: classification rule and error rates
3.3 Estimation of ROC curves
3.3.1 Empirical estimator
3.3.2 Parametric curve fitting
3.3.3 Nonparametric estimation
3.3.4 Binary regression methods
3.4 Sampling properties and confidence intervals
3.4.1 Empirical estimator
3.4.2 Parametric curve fitting
3.4.3 Nonparametric estimation
3.4.4 Binary regression methods
3.5 Estimating summary indices
3.5.1 Area under the curve (AUC)
Estimation
Confidence intervals
3.5.2 Partial area under the curve (PAUC)
3.5.3 Optimal classification threshold
3.5.4 Loss difference plots and the LC index
3.6 Further reading
Chapter 4: Further inference on single curves
4.1 Introduction
4.2 Tests of separation of P and N population scores
4.2.1 Kolmogorov-Smirnov test for the empirical ROC
4.2.2 Test of AUC = 0.5
4.3 Sample size calculations
4.3.1 Confidence intervals
4.3.2 Hypothesis tests
4.4 Errors in measurements
4.5 Further reading
Chapter 5: ROC curves and covariates
5.1 Introduction
5.2 Covariate adjustment of the ROC curve
5.2.1 Indirect adjustment
5.2.2 Direct adjustment
5.2.3 Applications
5.3 Covariate adjustment of summary statistics
5.3.1 Adjustment of AUC
5.3.2 Adjustment of partial AUC
5.3.3 Other summary statistics
5.3.4 Applications
5.4 Incremental value
5.5 Matching in case-control studies
5.6 Further reading
Chapter 6: Comparing ROC curves
6.1 Introduction
6.2 Comparing summary statistics of two ROC curves
6.3 Comparing AUCs for two ROC curves
6.4 Comparing entire curves
6.4.1 The binormal case
6.4.2 Nonparametric approach
6.4.3 Regression approaches
6.5 Identifying where ROC curves differ
6.6 Further reading
Chapter 7: Bayesian methods
7.1 Introduction
7.2 General ROC analysis
7.3 Meta-analysis
7.3.1 Introduction
7.3.2 Frequentist methods
7.3.3 Bayesian methods
Empirical Bayes
Full Bayes
7.4 Uncertain or unknown group labels
7.4.1 Introduction
7.4.2 Bayesian methods: parametric estimation
7.4.3 Bayesian methods: nonparametric estimation
7.5 Further reading
Chapter 8: Beyond the basics
8.1 Introduction
8.2 Alternatives to ROC curves
8.3 Convex hull ROC curves
8.4 ROC curves for more than two classes
8.5 Other issues
8.6 Further reading
Chapter 9: Design and interpretation issues
9.1 Introduction
9.2 Missing values
9.2.1 Missing value mechanisms
9.2.2 General missing value methodology
Deletion of observed values
Imputation of missing values
Maximum likelihood
9.2.3 Some implications for ROC studies
9.3 Bias in ROC studies
9.3.1 General
9.3.2 Verification bias
9.3.3 Reject inference
9.4 Choice of optimum threshold
9.5 Medical imaging
9.5.1 Design
9.5.2 Analysis and interpretation
9.6 Further reading
Chapter 10: Substantive applications
10.1 Introduction
10.2 Machine learning
10.3 Atmospheric sciences
10.4 Geosciences
10.5 Biosciences
10.6 Finance
10.7 Experimental psychology
10.8 Sociology

People also search for ROC Curves for Continuous Data 1st:

what is a good roc curve
    
how are roc curves generated
    
roc curve for continuous variable
    
roc curve continuous outcome
    
roc for continuous data

Tags: Wojtek J Krzanowski, David J Hand, ROC Curves, Continuous Data