title: Millions of random rules

authors: Pfahringer, Bernhard

subjects: computer science

abstract: In this paper we report on work in progress based on the induction of vast numbers of almost random rules. This work tries to combine and explore ideas from both Random Forests as well as Stochastic Discrimination. We describe a fast algorithm for generating almost random rules and study its performance. Rules are generated in such a way that all training examples are covered roughly by the same number of rules each. Rules themselves usually have a clear majority class among the examples they cover, but they are not limited in terms of either minimal coverage, nor minimal purity. A preliminary experimental evaluation indicates really promising results for both predictive accuracy as well as speed of induction, but at the expense of both large memory consumption as well as slow prediction. Finally, we discuss various directions for our future research.

text: Millions of random rules In this paper we report on work in progress based on the induction of vast numbers of almost random rules. This work tries to combine and explore ideas from both Random Forests as well as Stochastic Discrimination. We describe a fast algorithm for generating almost random rules and study its performance. Rules are generated in such a way that all training examples are covered roughly by the same number of rules each. Rules themselves usually have a clear majority class among the examples they cover, but they are not limited in terms of either minimal coverage, nor minimal purity. A preliminary experimental evaluation indicates really promising results for both predictive accuracy as well as speed of induction, but at the expense of both large memory consumption as well as slow prediction. Finally, we discuss various directions for our future research.

year: 2004

title: Development of models to predict Pinus radiata productivity throughout New Zealand

authors: Watt, Michael S.

subjects: New Zealand

abstract: Development of spatial surfaces describing variation in productivity across broad landscapes at a fine resolution would be of considerable use to forest managers as decision support tools to optimize productivity. In New Zealand, the two most widely used indices to quantify productivity of Pinus radiata D. Don are Site Index and 300 Index. Using an extensive national data set comprising a comprehensive set of national extent maps, multiple regression models and spatial surfaces of these indices for P. radiata were constructed. The final models accounted for 64% and 53%, respectively, of the variance in Site Index and 300 Index. For Site Index, variables included in the final model in order of importance were mean annual air temperature, fractional mean annual available root-zone water storage, mean annual windspeed, length and slope factor, categories describing Land Environments of New Zealand (LENZ), and major soil parent material. The variables included in the final model of 300 Index in order of importance included the degree of ground frost during autumn, fractional mean annual available root-zone water storage, categories describing LENZ, vegetation classification, foliar nitrogen, taxonomic soil order, and major soil parent material. These results highlight the utility of thematic spatial layers as driving variables in the development of productivity models.

text: Development of models to predict Pinus radiata productivity throughout New Zealand Development of spatial surfaces describing variation in productivity across broad landscapes at a fine resolution would be of considerable use to forest managers as decision support tools to optimize productivity. In New Zealand, the two most widely used indices to quantify productivity of Pinus radiata D. Don are Site Index and 300 Index. Using an extensive national data set comprising a comprehensive set of national extent maps, multiple regression models and spatial surfaces of these indices for P. radiata were constructed. The final models accounted for 64% and 53%, respectively, of the variance in Site Index and 300 Index. For Site Index, variables included in the final model in order of importance were mean annual air temperature, fractional mean annual available root-zone water storage, mean annual windspeed, length and slope factor, categories describing Land Environments of New Zealand (LENZ), and major soil parent material. The variables included in the final model of 300 Index in order of importance included the degree of ground frost during autumn, fractional mean annual available root-zone water storage, categories describing LENZ, vegetation classification, foliar nitrogen, taxonomic soil order, and major soil parent material. These results highlight the utility of thematic spatial layers as driving variables in the development of productivity models.

year: 2010

title: Can large taonga bivalves speed up recovery in degraded estuaries?

authors: Prinz, Natalie

abstract: THE QUESTION:
Will there introduction of adult, long-lived bivalves with differing functional traits speed up recovery of degraded soft sediment habitats in estuaries?
RESULTS:
Average bivalve survival after one year was 18% in + tuangi plot sand 59% in + hanikura plots. Sediment oxygen consumption (SOC) after one month was enhanced by 116% in treatments containing tuangi compared to control treatments. After one year those were similar to ambient levels, still showed higher SOC than control plots.

text: Can large taonga bivalves speed up recovery in degraded estuaries? THE QUESTION:
Will there introduction of adult, long-lived bivalves with differing functional traits speed up recovery of degraded soft sediment habitats in estuaries?
RESULTS:
Average bivalve survival after one year was 18% in + tuangi plot sand 59% in + hanikura plots. Sediment oxygen consumption (SOC) after one month was enhanced by 116% in treatments containing tuangi compared to control treatments. After one year those were similar to ambient levels, still showed higher SOC than control plots.

year: 2023