title: The Creation of Sustainable Development: What it means to CFOs in New Zealand

authors: Dimitrov, Dara

subjects: sustainability

abstract: Abstract currently unavailable

text: The Creation of Sustainable Development: What it means to CFOs in New Zealand Abstract currently unavailable

year: 2009

title: An Empirical Comparison of Exact Nearest Neighbour Algorithms

authors: Frank, Eibe

subjects: computer science

abstract: Bagging is an ensemble learning method that has proved to be a useful tool in the arsenal of machine learning practitioners. Commonly applied in conjunction with decision tree learners to build an ensemble of decision trees, it often leads to reduced errors in the predictions when compared to using a single tree. A single tree is built from a training set of size N. Bagging is based on the idea that, ideally, we would like to eliminate the variance due to a particular training set by combining trees built from all training sets of size N. However, in practice, only one training set is available, and bagging simulates this platonic method by sampling with replacement from the original training data to form new training sets. In this paper we pursue the idea of sampling from a kernel density estimator of the underlying distribution to form new training sets, in addition to sampling from the data itself. This can be viewed as “smearing out” the resampled training data to generate new datasets, and the amount of “smear” is controlled by a parameter. We show that the resulting method, called “input smearing”, can lead to improved results when compared to bagging. We present results for both classification and regression problems.

text: An Empirical Comparison of Exact Nearest Neighbour Algorithms Bagging is an ensemble learning method that has proved to be a useful tool in the arsenal of machine learning practitioners. Commonly applied in conjunction with decision tree learners to build an ensemble of decision trees, it often leads to reduced errors in the predictions when compared to using a single tree. A single tree is built from a training set of size N. Bagging is based on the idea that, ideally, we would like to eliminate the variance due to a particular training set by combining trees built from all training sets of size N. However, in practice, only one training set is available, and bagging simulates this platonic method by sampling with replacement from the original training data to form new training sets. In this paper we pursue the idea of sampling from a kernel density estimator of the underlying distribution to form new training sets, in addition to sampling from the data itself. This can be viewed as “smearing out” the resampled training data to generate new datasets, and the amount of “smear” is controlled by a parameter. We show that the resulting method, called “input smearing”, can lead to improved results when compared to bagging. We present results for both classification and regression problems.

year: 2007

title: The Marist missionaries' first encounters with inhabitants of the Pacific

authors: William, Jennings

subjects: missionaries

abstract: Missionaries of the French-based Society of Mary (Marists) arrived in the Pacific in the late 1830s. Reports by European travellers and missionaries had told the first Marists to expect Pacific peoples who were either cannibals or noble savages. Their encounter with recently-converted Mangarevans in the Gambier Islands led them to believe that idyllic Christian societies could be created in the South Pacific. This belief influenced the first Marists' descriptions of Pacific peoples, notably New Zealand Maori. The Marists consequently emphasised the noble savage trope and downplayed cannibalism. They also displayed a relatively tolerant attitude towards indigenous practices.

text: The Marist missionaries' first encounters with inhabitants of the Pacific Missionaries of the French-based Society of Mary (Marists) arrived in the Pacific in the late 1830s. Reports by European travellers and missionaries had told the first Marists to expect Pacific peoples who were either cannibals or noble savages. Their encounter with recently-converted Mangarevans in the Gambier Islands led them to believe that idyllic Christian societies could be created in the South Pacific. This belief influenced the first Marists' descriptions of Pacific peoples, notably New Zealand Maori. The Marists consequently emphasised the noble savage trope and downplayed cannibalism. They also displayed a relatively tolerant attitude towards indigenous practices.

year: 2013