Browsing by Subject "model selection"
Now showing items 1-4 of 4
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Efficient Model Selection in Linear and Non-Linear Quantile Regression by Cross-Validation
(2016-04-19)Check loss function is used to define quantile regression. In the prospect of cross validation, it is also employed as a validation function when underlying truth is unknown. However, our empirical study indicates that the ... -
Experiment Databases: Creating a New Platform for Meta-Learning Research
(University of Porto, 2008)Many studies in machine learning try to investigate what makes an algorithm succeed or fail on certain datasets. However, the field is still evolving relatively quickly, and new algorithms, preprocessing methods, learning ... -
Meta-Learning and the Full Model Selection Problem
(University of Waikato, 2014)When working as a data analyst, one of my daily tasks is to select appropriate tools from a set of existing data analysis techniques in my toolbox, including data preprocessing, outlier detection, feature selection, learning ... -
A novel two stage scheme utilizing the test set for model selection in text classification
(University of Technology, Sydney, 2005)Text classification is a natural application domain for semi-supervised learning, as labeling documents is expensive, but on the other hand usually an abundance of unlabeled documents is available. We describe a novel ...
