Quantitative behaviour analysis requires the classification of behaviour to produce the basic data. In practice, much of this work will be performed by multiple observers, and maximising inter-observer consistency is of particular importance. Another discipline where consistency in classification is vital is biological taxonomy. A classification tool of great utility, the binary key, is designed to simplify the classification decision process and ensure consistent identification of proper categories. We show how this same decision-making tool - the binary key - can be used to promote consistency in the classification of behaviour. The construction of a binary key also ensures that the categories in which behaviour is classified are complete...
A new simple scoring technique is developed in a binary supervised classification context when only ...
Classification problems in machine learning involve assigning labels to various kinds of output type...
This dissertation develops and analyzes active learning algorithms for binary classification problem...
Quantitative behaviour analysis requires the classification of behaviour to produce the basic data. ...
Quantitative behaviour analysis requires the classification of behaviour to produce the basic data. ...
Quantitative behaviour analysis requires the classification of behaviour to produce the basic data. ...
Abstract. Binary classification methods can be generalized in many ways to handle multiple classes. ...
The classification of behaviour has historically been done using one of the two approaches, either t...
Vision systems are now delivering real-time tracked and classified data from which behaviours can be...
Automated quantification of behavior is increasingly prevalent in neuroscience research. Human judgm...
Vision systems are now delivering real-time tracked and classified data from which behaviours can be...
Variable selection is an essential tool for gaining knowledge on a problem or phenomenon, by identif...
The classifier system framework is a general-purpose approach to learning and representation designe...
Making binary decisions is a common data analytical task in scientific research and industrial appli...
In the pattern recognition literature, Huang and Suen introduced the “multinomial” rule for fusion o...
A new simple scoring technique is developed in a binary supervised classification context when only ...
Classification problems in machine learning involve assigning labels to various kinds of output type...
This dissertation develops and analyzes active learning algorithms for binary classification problem...
Quantitative behaviour analysis requires the classification of behaviour to produce the basic data. ...
Quantitative behaviour analysis requires the classification of behaviour to produce the basic data. ...
Quantitative behaviour analysis requires the classification of behaviour to produce the basic data. ...
Abstract. Binary classification methods can be generalized in many ways to handle multiple classes. ...
The classification of behaviour has historically been done using one of the two approaches, either t...
Vision systems are now delivering real-time tracked and classified data from which behaviours can be...
Automated quantification of behavior is increasingly prevalent in neuroscience research. Human judgm...
Vision systems are now delivering real-time tracked and classified data from which behaviours can be...
Variable selection is an essential tool for gaining knowledge on a problem or phenomenon, by identif...
The classifier system framework is a general-purpose approach to learning and representation designe...
Making binary decisions is a common data analytical task in scientific research and industrial appli...
In the pattern recognition literature, Huang and Suen introduced the “multinomial” rule for fusion o...
A new simple scoring technique is developed in a binary supervised classification context when only ...
Classification problems in machine learning involve assigning labels to various kinds of output type...
This dissertation develops and analyzes active learning algorithms for binary classification problem...