title: Help! virtue profiles and horses for courses

authors: Lumsden, David

abstract: Glen Pettigrove addresses the proportionality principle in ethics, the principle that “our actions, attitudes, or emotions should be proportional to the degree of value present in the object or events to which they are responding” [p. 1]. He argues this is inconsistent with some familiar features of common-sense morality. In response, he brings virtuous character into the picture, a move we support but wish to modify. We show that certain helping actions should be guided by whether one has the virtue profile most suited to the situation from amongst a surrounding network of people.

text: Help! virtue profiles and horses for courses Glen Pettigrove addresses the proportionality principle in ethics, the principle that “our actions, attitudes, or emotions should be proportional to the degree of value present in the object or events to which they are responding” [p. 1]. He argues this is inconsistent with some familiar features of common-sense morality. In response, he brings virtuous character into the picture, a move we support but wish to modify. We show that certain helping actions should be guided by whether one has the virtue profile most suited to the situation from amongst a surrounding network of people.

year: 2021

title: Efficient data stream classification via probabilistic adaptive windows

authors: Bifet, Albert

subjects: computer science

abstract: In the context of a data stream, a classifier must be able to learn from a theoretically-infinite stream of examples using limited time and memory, while being able to predict at any point. Many methods deal with this problem by basing their model on a window of examples. We introduce a probabilistic adaptive window (PAW) for data-stream learning, which improves this windowing technique with a mechanism to include older examples as well as the most recent ones, thus maintaining information on past concept drifts while being able to adapt quickly to new ones. We exemplify PAW with lazy learning methods in two variations: one to handle concept drift explicitly, and the other to add classifier diversity using an ensemble. Along with the standard measures of accuracy and time and memory use, we compare classifiers against state-of-the-art classifiers from the data-stream literature.

text: Efficient data stream classification via probabilistic adaptive windows In the context of a data stream, a classifier must be able to learn from a theoretically-infinite stream of examples using limited time and memory, while being able to predict at any point. Many methods deal with this problem by basing their model on a window of examples. We introduce a probabilistic adaptive window (PAW) for data-stream learning, which improves this windowing technique with a mechanism to include older examples as well as the most recent ones, thus maintaining information on past concept drifts while being able to adapt quickly to new ones. We exemplify PAW with lazy learning methods in two variations: one to handle concept drift explicitly, and the other to add classifier diversity using an ensemble. Along with the standard measures of accuracy and time and memory use, we compare classifiers against state-of-the-art classifiers from the data-stream literature.

year: 2013

title: A late-Holocene and prehistoric record of environmental change from Lake Waikaremoana, New Zealand

authors: Newnham, Rewi M.

subjects: Palynology

abstract: Further evidence in support of a late pre-European (Polynesian) settlement of New Zealand is provided by an 1850-year-long tephropalynological record from a remote region in New Zealand's North Island. The earliest unequivocally anthropogenic forest clearance is estimated from sedimentation rates to have occurred c. 375 14C years BP (c. ad 1523–1631), although the radiocarbon chronology, shown by tephrochron ology to be erroneous due to hard-water effects, suggested this occurred c. 900 years earlier. Delineation of the anthropogenic era, and the distinction between human activity and other agents of environmental change in the pollen/spore diagram, are supported by cluster analysis and detrended correspondence analysis. Two distinct phases of forest clearance are evident during the pre-European era, reflecting local changes either in population pressure or settlement patterns. We note that the lull between the two phases of forest clearance coincides with the maximum of the ‘Little Ice Age’ within the period c. late ad 1600s to early 1800s.

text: A late-Holocene and prehistoric record of environmental change from Lake Waikaremoana, New Zealand Further evidence in support of a late pre-European (Polynesian) settlement of New Zealand is provided by an 1850-year-long tephropalynological record from a remote region in New Zealand's North Island. The earliest unequivocally anthropogenic forest clearance is estimated from sedimentation rates to have occurred c. 375 14C years BP (c. ad 1523–1631), although the radiocarbon chronology, shown by tephrochron ology to be erroneous due to hard-water effects, suggested this occurred c. 900 years earlier. Delineation of the anthropogenic era, and the distinction between human activity and other agents of environmental change in the pollen/spore diagram, are supported by cluster analysis and detrended correspondence analysis. Two distinct phases of forest clearance are evident during the pre-European era, reflecting local changes either in population pressure or settlement patterns. We note that the lull between the two phases of forest clearance coincides with the maximum of the ‘Little Ice Age’ within the period c. late ad 1600s to early 1800s.

year: 1998