Add to ORKGThis paper presents MMM and MMC, two methods for combining knowledge from a variety of prediction models. Some of these models may have been created by hand while others may be the result of empirical learning over an available set of data. The approach consists of learning a set of "Referees", one for each prediction model, that characterize the situations in which each of the models is able to make correct predictions. In future instances, these referees are first consulted to select the most appropriate prediction model, and the prediction of the selected model is then returned. Experimental results on the audiology domain show that using referees can help obtain higher accuracies than those obtained by any of the individual pr...
The research describes the use of both descriptive and predictive algorithms for better accurate pre...
Prediction is the key objective of many machine learning applications. Accurate, reliable and robust...
Thesis (Ph.D.)--University of Washington, 2022Machine learning prediction and explanation systems of...
Multiple approaches have been developed for improving predictive performance of a system by creating...
Many applications of supervised machine learning consist of training data with a large number of fea...
Data analysis usually aims to identify a particular signal, such as an intervention effect. Conventi...
In the previous chapter, you have learned how to prepare your data before you start the process of g...
ABSTRACT - Traditional statistical models as tools for summarizing patterns and regularities in obse...
Data analysis usually aims to identify a particular signal, such as an intervention effect. Conventi...
Abstract: Machine Learning generates programs that make predictions and informed decisions about com...
Machine learning approaches for prediction play an integral role in modern-day decision supports sys...
Pre-requisites to better understand the chapter: knowledge of the major steps and procedures of deve...
Here we give a technique for online prediction that uses different model selection principles (MSP's...
One fundamental task of machine learning is to predict output responses y from input data x. However...
Many machine learning techniques remain ''black boxes'' because, despite their high predictive perfo...
The research describes the use of both descriptive and predictive algorithms for better accurate pre...
Prediction is the key objective of many machine learning applications. Accurate, reliable and robust...
Thesis (Ph.D.)--University of Washington, 2022Machine learning prediction and explanation systems of...
Multiple approaches have been developed for improving predictive performance of a system by creating...
Many applications of supervised machine learning consist of training data with a large number of fea...
Data analysis usually aims to identify a particular signal, such as an intervention effect. Conventi...
In the previous chapter, you have learned how to prepare your data before you start the process of g...
ABSTRACT - Traditional statistical models as tools for summarizing patterns and regularities in obse...
Data analysis usually aims to identify a particular signal, such as an intervention effect. Conventi...
Abstract: Machine Learning generates programs that make predictions and informed decisions about com...
Machine learning approaches for prediction play an integral role in modern-day decision supports sys...
Pre-requisites to better understand the chapter: knowledge of the major steps and procedures of deve...
Here we give a technique for online prediction that uses different model selection principles (MSP's...
One fundamental task of machine learning is to predict output responses y from input data x. However...
Many machine learning techniques remain ''black boxes'' because, despite their high predictive perfo...
The research describes the use of both descriptive and predictive algorithms for better accurate pre...
Prediction is the key objective of many machine learning applications. Accurate, reliable and robust...
Thesis (Ph.D.)--University of Washington, 2022Machine learning prediction and explanation systems of...