title: Prediction Intervals for Class Probabilities

authors: Yu, Xiaofeng

subjects: bayesian classifier

abstract: Prediction intervals for class probabilities are of interest in machine learning because they
can quantify the uncertainty about the class probability estimate for a test instance. The
idea is that all likely class probability values of the test instance are included, with a
pre-specified confidence level, in the calculated prediction interval. This thesis proposes a
probabilistic model for calculating such prediction intervals. Given the unobservability of
class probabilities, a Bayesian approach is employed to derive a complete distribution of the
class probability of a test instance based on a set of class observations of training instances
in the neighbourhood of the test instance. A random decision tree ensemble learning
algorithm is also proposed, whose prediction output constitutes the neighbourhood that
is used by the Bayesian model to produce a PI for the test instance. The Bayesian
model, which is used in conjunction with the ensemble learning algorithm and the standard
nearest-neighbour classifier, is evaluated on artificial datasets and modified real datasets.

text: Prediction Intervals for Class Probabilities Prediction intervals for class probabilities are of interest in machine learning because they
can quantify the uncertainty about the class probability estimate for a test instance. The
idea is that all likely class probability values of the test instance are included, with a
pre-specified confidence level, in the calculated prediction interval. This thesis proposes a
probabilistic model for calculating such prediction intervals. Given the unobservability of
class probabilities, a Bayesian approach is employed to derive a complete distribution of the
class probability of a test instance based on a set of class observations of training instances
in the neighbourhood of the test instance. A random decision tree ensemble learning
algorithm is also proposed, whose prediction output constitutes the neighbourhood that
is used by the Bayesian model to produce a PI for the test instance. The Bayesian
model, which is used in conjunction with the ensemble learning algorithm and the standard
nearest-neighbour classifier, is evaluated on artificial datasets and modified real datasets.

year: 2007

title: Compression by induction of hierarchical grammars

authors: Nevill-Manning, Craig G.

subjects: Machine learning

abstract: This paper describes a technique that develops models of symbol sequences in the form of small, human-readable, hierarchical grammars. The grammars are both semantically plausible and compact. The technique can induce structure from a variety of different kinds of sequence, and examples are given of models derived from English text, C source code and a file of numeric data. This paper explains the grammatical induction technique, demonstrates its application to three very different sequences, evaluates its compression performance, and concludes by briefly discussing its use as method of knowledge acquisition.

text: Compression by induction of hierarchical grammars This paper describes a technique that develops models of symbol sequences in the form of small, human-readable, hierarchical grammars. The grammars are both semantically plausible and compact. The technique can induce structure from a variety of different kinds of sequence, and examples are given of models derived from English text, C source code and a file of numeric data. This paper explains the grammatical induction technique, demonstrates its application to three very different sequences, evaluates its compression performance, and concludes by briefly discussing its use as method of knowledge acquisition.

year: 1993

title: Too many Māori and Asian people are drowning – can better cultural understanding reverse the trend?

authors: Wheaton, Belinda

abstract: The article discusses the high rate of drownings in New Zealand, particularly among Māori and Asian communities. It highlights the need for culturally specific water safety education to address this issue. The Asian community, in particular, includes many first-generation migrants who may lack water skills due to their upbringing and fear of water. Overprotectiveness towards children around water is also common among Asian parents. The article emphasizes the importance of providing support and learning opportunities to help Asian migrants develop water skills and feel more comfortable in outdoor activities. Additionally, it mentions the declining water skills among New Zealand children in general and the need for better resourcing of school programs and community initiatives like ActivAsian. Culturally relevant knowledge and education are deemed crucial in changing attitudes and behaviors towards water safety. The article stresses that making New Zealand's beaches and waterways safe for all residents, including migrants, requires targeted funding and a collaborative effort to prevent tragic drowning incidents.

text: Too many Māori and Asian people are drowning – can better cultural understanding reverse the trend? The article discusses the high rate of drownings in New Zealand, particularly among Māori and Asian communities. It highlights the need for culturally specific water safety education to address this issue. The Asian community, in particular, includes many first-generation migrants who may lack water skills due to their upbringing and fear of water. Overprotectiveness towards children around water is also common among Asian parents. The article emphasizes the importance of providing support and learning opportunities to help Asian migrants develop water skills and feel more comfortable in outdoor activities. Additionally, it mentions the declining water skills among New Zealand children in general and the need for better resourcing of school programs and community initiatives like ActivAsian. Culturally relevant knowledge and education are deemed crucial in changing attitudes and behaviors towards water safety. The article stresses that making New Zealand's beaches and waterways safe for all residents, including migrants, requires targeted funding and a collaborative effort to prevent tragic drowning incidents.

year: 2022-12-20