Journal ArticleDOI
Cross-Validatory Choice and Assessment of Statistical Predictions
TLDR
In this article, a generalized form of the cross-validation criterion is applied to the choice and assessment of prediction using the data-analytic concept of a prescription, and examples used to illustrate the application are drawn from the problem areas of univariate estimation, linear regression and analysis of variance.Abstract:
SUMMARY A generalized form of the cross-validation criterion is applied to the choice and assessment of prediction using the data-analytic concept of a prescription. The examples used to illustrate the application are drawn from the problem areas of univariate estimation, linear regression and analysis of variance.read more
Citations
More filters
Book
Data Mining: Concepts and Techniques
TL;DR: This book presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects, and provides a comprehensive, practical look at the concepts and techniques you need to get the most out of real business data.
Book
Neural networks for pattern recognition
TL;DR: This is the first comprehensive treatment of feed-forward neural networks from the perspective of statistical pattern recognition, and is designed as a text, with over 100 exercises, to benefit anyone involved in the fields of neural computation and pattern recognition.
Journal ArticleDOI
Deep learning in neural networks
TL;DR: This historical survey compactly summarizes relevant work, much of it from the previous millennium, review deep supervised learning, unsupervised learning, reinforcement learning & evolutionary computation, and indirect search for short programs encoding deep and large networks.
Journal ArticleDOI
PLS-SEM: Indeed a Silver Bullet
TL;DR: The authors conclude that PLS-SEM path modeling, if appropriately applied, is indeed a "silver bullet" for estimating causal models in many theoretical models and empirical data situations.
Journal ArticleDOI
A tutorial on support vector regression
TL;DR: This tutorial gives an overview of the basic ideas underlying Support Vector (SV) machines for function estimation, and includes a summary of currently used algorithms for training SV machines, covering both the quadratic programming part and advanced methods for dealing with large datasets.
References
More filters
Book
Statistical Theories of Mental Test Scores
TL;DR: In this paper, the authors present a survey of test theory models and their application in the field of mental test analysis. But the focus of the survey is on test-score theories and models, and not the practical applications and limitations of each model studied.
Book
Optimal Statistical Decisions
TL;DR: In this article, the authors present a survey of probability theory in the context of sample spaces and decision problems, including the following: 1.1 Experiments and Sample Spaces, and Probability 2.2.3 Random Variables, Random Vectors and Distributions Functions.
Journal ArticleDOI
A predictive approach to the random effect model
TL;DR: In this paper, two simple estimators are derived for the means of the random effect model by means of predictive sample reuse, which are applied to two sets of data in the literature and compared with several other procedures.
Journal ArticleDOI
Estimation of Error Rates in Discriminant Analysis
TL;DR: In this article, several methods of estimating error rates in discriminant analysis are evaluated by sampling methods, and two methods in most common use are found to be significantly poorer than some new methods that are proposed.
Journal ArticleDOI
The Relationship Between Variable Selection and Data Agumentation and a Method for Prediction
TL;DR: It is shown that data augmentation provides a rather general formulation for the study of biased prediction techniques using multiple linear regression and a way to obtain predictors given a credible criterion of good prediction is proposed.