title: Applying machine learning to programming by demonstration

authors: Paynter, Gordon W.

subjects: computer science

abstract: ‘Familiar’ is a tool that helps end-users automate iterative tasks in their applications by showing examples of what they want to do. It observes the user’s actions, predicts what they will do next, and then offers to complete their task. Familiar learns in two ways. First, it creates a model, based on data gathered from training tasks, that selects the best prediction from among several candidates. Experiments show that decision trees outperform heuristic methods, and can be further improved by incrementally updating the classifier at task time. Second, it uses decision stumps inferred from analogous examples in the event trace to predict the parameters of conditional rules. Because data is sparse—for most users balk at giving more than a few training examples—permutation tests are used to calculate the statistical significance of each stump, successfully eliminating bias towards attributes with many different values.

text: Applying machine learning to programming by demonstration ‘Familiar’ is a tool that helps end-users automate iterative tasks in their applications by showing examples of what they want to do. It observes the user’s actions, predicts what they will do next, and then offers to complete their task. Familiar learns in two ways. First, it creates a model, based on data gathered from training tasks, that selects the best prediction from among several candidates. Experiments show that decision trees outperform heuristic methods, and can be further improved by incrementally updating the classifier at task time. Second, it uses decision stumps inferred from analogous examples in the event trace to predict the parameters of conditional rules. Because data is sparse—for most users balk at giving more than a few training examples—permutation tests are used to calculate the statistical significance of each stump, successfully eliminating bias towards attributes with many different values.

year: 2004

title: Comparative phylogeography in the genomic age: Opportunities and challenges

authors: McGaughran, Angela

subjects: community genomics

abstract: Aim: We consider the opportunities and challenges comparative phylogeography (CP) faces in the genomic age to determine: (1) how we can maximise the potential of big CP analyses to advance biogeographic and macroevolutionary theory; and (2) what we can, and will struggle, to achieve using CP approaches in this era of genomics. 
Location: World-wide. 
Taxon: All. 
Methods: We review the literature to discuss the future of CP - particularly examining CP insights enabled by genomics that may not be possible for single species and/or few molecular markers. We focus on how geography and species' natural histories interact to yield congruent and incongruent patterns of neutral and adaptive processes in the context of both historical and recent rapid evolution. We also consider how CP genomic data are being stored, accessed, and shared. 
Results: With the widespread availability of genomic data, the shift from a single- to a multi-locus perspective is resulting in detailed historical inferences and an improved statistical rigour in phylogeography. However, the time and effort required for collecting co-distributed species and accruing species-specific ecological knowledge continue to be limiting factors. Bioinformatic skills and user-friendly analytical tools, alongside the computational infrastructure required for big data, can also be limiting. 
Main conclusions: Over the last ~35 years, there has been much progress in understanding how intraspecific genetic variation is geographically distributed. The next major steps in CP will be to incorporate evolutionary processes and community perspectives to account for patterns and responses among co-distributed species and across temporal scales, including those related to anthropogenic change. However, the full potential of CP will only be realised if we employ robust study designs within a sound comparative framework. We advocate that phylogeographers adopt such consistent approaches to enhance future comparisons to present-day findings.

text: Comparative phylogeography in the genomic age: Opportunities and challenges Aim: We consider the opportunities and challenges comparative phylogeography (CP) faces in the genomic age to determine: (1) how we can maximise the potential of big CP analyses to advance biogeographic and macroevolutionary theory; and (2) what we can, and will struggle, to achieve using CP approaches in this era of genomics. 
Location: World-wide. 
Taxon: All. 
Methods: We review the literature to discuss the future of CP - particularly examining CP insights enabled by genomics that may not be possible for single species and/or few molecular markers. We focus on how geography and species' natural histories interact to yield congruent and incongruent patterns of neutral and adaptive processes in the context of both historical and recent rapid evolution. We also consider how CP genomic data are being stored, accessed, and shared. 
Results: With the widespread availability of genomic data, the shift from a single- to a multi-locus perspective is resulting in detailed historical inferences and an improved statistical rigour in phylogeography. However, the time and effort required for collecting co-distributed species and accruing species-specific ecological knowledge continue to be limiting factors. Bioinformatic skills and user-friendly analytical tools, alongside the computational infrastructure required for big data, can also be limiting. 
Main conclusions: Over the last ~35 years, there has been much progress in understanding how intraspecific genetic variation is geographically distributed. The next major steps in CP will be to incorporate evolutionary processes and community perspectives to account for patterns and responses among co-distributed species and across temporal scales, including those related to anthropogenic change. However, the full potential of CP will only be realised if we employ robust study designs within a sound comparative framework. We advocate that phylogeographers adopt such consistent approaches to enhance future comparisons to present-day findings.

year: 2022

title: Ko Te Ika-a-Māui rānei?

authors: Takurua, Nātana

abstract: Tēnei au te noho nei me te kōroiroi o whakaaro i roto i a Hinengaro. He aha rā te take kāore i mau mai ai ngā ingoa Māori tūturu, whai mana nei i te taenga mai o te Pākehā ki Aotearoa nei? Nā wai i kī ka hurihia ngā ingoa kua tapaina noatia e ngā mātua tīpuna kia noho ko te North me te South
Island?

text: Ko Te Ika-a-Māui rānei? Tēnei au te noho nei me te kōroiroi o whakaaro i roto i a Hinengaro. He aha rā te take kāore i mau mai ai ngā ingoa Māori tūturu, whai mana nei i te taenga mai o te Pākehā ki Aotearoa nei? Nā wai i kī ka hurihia ngā ingoa kua tapaina noatia e ngā mātua tīpuna kia noho ko te North me te South
Island?

year: 2009