title: A simple approach to ordinal classification

authors: Frank, Eibe

abstract: Machine learning methods for classification problems commonly assume that the class values are unordered. However, in many practical applications, the class values do exhibit a natural order—for example, when learning how to grade. The standard approach to ordinal classification converts the class value into a numeric quantity and applies a regression learner to the transformed data, translating the output back into a discrete class value in a post-processing step. A disadvantage of this method is that it can only be applied in conjunction with a regression scheme.

In this paper, we present a simple method that enables standard classification algorithms to make use of ordering information in class attributes. By applying it in conjunction with a decision tree learner, we show that it outperforms the naive approach, which treats the class values as an unordered set. Compared to special-purpose algorithms for ordinal classification, our method has the advantage that it can be applied without any modification to the underlying learning scheme.

text: A simple approach to ordinal classification Machine learning methods for classification problems commonly assume that the class values are unordered. However, in many practical applications, the class values do exhibit a natural order—for example, when learning how to grade. The standard approach to ordinal classification converts the class value into a numeric quantity and applies a regression learner to the transformed data, translating the output back into a discrete class value in a post-processing step. A disadvantage of this method is that it can only be applied in conjunction with a regression scheme.

In this paper, we present a simple method that enables standard classification algorithms to make use of ordering information in class attributes. By applying it in conjunction with a decision tree learner, we show that it outperforms the naive approach, which treats the class values as an unordered set. Compared to special-purpose algorithms for ordinal classification, our method has the advantage that it can be applied without any modification to the underlying learning scheme.

year: 2001

title: Advances in modeling trait-based plant community assembly

authors: Laughlin, Daniel C.

subjects: environmental filtering

abstract: In this review, we examine two new trait-based models of community assembly that predict the relative abundance of species from a regional species pool. The models use fundamentally different mathematical approaches and the predictions can differ considerably. Maxent obtains the most even probability distribution subject to community-weighted mean trait constraints. Traitspace predicts low probabilities for any species whose trait distribution does not pass through the environmental filter. Neither model maximizes functional diversity because of the emphasis on environmental filtering over limiting similarity. Traitspace can test for the effects of limiting similarity by explicitly incorporating intraspecific trait variation. The range of solutions in both models could be used to define the range of natural variability of community composition in restoration projects.

text: Advances in modeling trait-based plant community assembly In this review, we examine two new trait-based models of community assembly that predict the relative abundance of species from a regional species pool. The models use fundamentally different mathematical approaches and the predictions can differ considerably. Maxent obtains the most even probability distribution subject to community-weighted mean trait constraints. Traitspace predicts low probabilities for any species whose trait distribution does not pass through the environmental filter. Neither model maximizes functional diversity because of the emphasis on environmental filtering over limiting similarity. Traitspace can test for the effects of limiting similarity by explicitly incorporating intraspecific trait variation. The range of solutions in both models could be used to define the range of natural variability of community composition in restoration projects.

year: 2013-10

title: Radiocarbon dates on desiccated moa (Dinornithiformes) flesh from Inland Otago, New Zealand

authors: Anderson, Atholl

subjects: New Zealand

abstract: Remains of soft tissues from extinct moa (Dinornithiformes), mainly desiccated sinew, muscle, skin, and feathers have been recovered rather seldom but their distribution is distinctive. Of 22 records of such finds accumulated between 1864 and 1987, 15 came from inland Otago (Anderson 1989: 67–68, Table 5.2), west of Dunedin in the southern South Island. Most were found in the late nineteenth century (13 records) in rockshelters, clefts or alluvial sediments and were regarded at the time as evidence of the survival of moa up to about AD 1800 (Hutton and Coughtrey 1874a). Improbable as this latter point is, it has not been tested by radiocarbon dating until now. Our particular impetus to do so, however, arises in another way. It is from research, again largely within inland Otago, on Maori artefacts which have also been made from various other kinds of soft tissues (flax, grasses, dog skin, bird skin, feathers etc.). A series of accelerator mass spectrometry (AMS) radiocarbon dates on these (Anderson et al., n.d.) shows that they are exclusively late, post-AD 1650, which begs the question of why the age range does not extend across the full prehistoric period, beginning about AD 1300.

text: Radiocarbon dates on desiccated moa (Dinornithiformes) flesh from Inland Otago, New Zealand Remains of soft tissues from extinct moa (Dinornithiformes), mainly desiccated sinew, muscle, skin, and feathers have been recovered rather seldom but their distribution is distinctive. Of 22 records of such finds accumulated between 1864 and 1987, 15 came from inland Otago (Anderson 1989: 67–68, Table 5.2), west of Dunedin in the southern South Island. Most were found in the late nineteenth century (13 records) in rockshelters, clefts or alluvial sediments and were regarded at the time as evidence of the survival of moa up to about AD 1800 (Hutton and Coughtrey 1874a). Improbable as this latter point is, it has not been tested by radiocarbon dating until now. Our particular impetus to do so, however, arises in another way. It is from research, again largely within inland Otago, on Maori artefacts which have also been made from various other kinds of soft tissues (flax, grasses, dog skin, bird skin, feathers etc.). A series of accelerator mass spectrometry (AMS) radiocarbon dates on these (Anderson et al., n.d.) shows that they are exclusively late, post-AD 1650, which begs the question of why the age range does not extend across the full prehistoric period, beginning about AD 1300.

year: 2010