title: Clustering for classification

authors: Evans, Reuben James Emmanuel

subjects: computer science

abstract: Advances in technology have provided industry with an array of devices for collecting data. The frequency and scale of data collection means that there are now many large datasets being generated. To find patterns in these datasets it would be useful to be able to apply modern methods of classification such as support vector machines. Unfortunately these methods are computationally expensive, quadratic in the number of data points in fact, so cannot be applied directly. This paper proposes a framework whereby a variety of clustering methods can be used to summarise datasets, that is, reduce them to a smaller but still representative dataset so that advanced methods can be applied. It compares the results of using this framework against using random selection on a large number of classification problems. Results show that clustering prior to classification is beneficial when employing a sophisticated classifier however when the classifier is simple the benefits over random selection are not justified given the added cost of clustering. The results also show that for each dataset it is important to choose a clustering method carefully.

text: Clustering for classification Advances in technology have provided industry with an array of devices for collecting data. The frequency and scale of data collection means that there are now many large datasets being generated. To find patterns in these datasets it would be useful to be able to apply modern methods of classification such as support vector machines. Unfortunately these methods are computationally expensive, quadratic in the number of data points in fact, so cannot be applied directly. This paper proposes a framework whereby a variety of clustering methods can be used to summarise datasets, that is, reduce them to a smaller but still representative dataset so that advanced methods can be applied. It compares the results of using this framework against using random selection on a large number of classification problems. Results show that clustering prior to classification is beneficial when employing a sophisticated classifier however when the classifier is simple the benefits over random selection are not justified given the added cost of clustering. The results also show that for each dataset it is important to choose a clustering method carefully.

year: 2011

title: Spatial variation in ‘Hayward’ kiwifruit dry matter content within a growing region across seasons

authors: Woodward, Tim J.

subjects: kiwifruit

abstract: Between-orchard variation in fruit dry matter (DM) content at harvest of 341 commercial ‘Hayward’ kiwifruit orchards was spatially modelled across a production region over consecutive growing seasons (2003–08). Within seasons there were spatial patterns to the distribution of fruit DM between orchards. The temporal consistency of the spatial variation enabled segregation of the production region into two geographic zones which contained orchards that consistently produced fruit of distinct DM both within and across seasons. The differences in fruit DM between geographic zones were statistically significant, but were not of sufficient magnitude to be of commercial interest. Although the location of an orchard within the production region had an effect on the DM of the fruit produced, orchard location was not predictive of fruit DM. Therefore, it is concluded that in this situation zonation between orchards should not be where the effort in managing variation in fruit quality is concentrated.

text: Spatial variation in ‘Hayward’ kiwifruit dry matter content within a growing region across seasons Between-orchard variation in fruit dry matter (DM) content at harvest of 341 commercial ‘Hayward’ kiwifruit orchards was spatially modelled across a production region over consecutive growing seasons (2003–08). Within seasons there were spatial patterns to the distribution of fruit DM between orchards. The temporal consistency of the spatial variation enabled segregation of the production region into two geographic zones which contained orchards that consistently produced fruit of distinct DM both within and across seasons. The differences in fruit DM between geographic zones were statistically significant, but were not of sufficient magnitude to be of commercial interest. Although the location of an orchard within the production region had an effect on the DM of the fruit produced, orchard location was not predictive of fruit DM. Therefore, it is concluded that in this situation zonation between orchards should not be where the effort in managing variation in fruit quality is concentrated.

year: 2011

title: The TOHU framework: Sensing and interpreting tohu to heal from trauma

authors: McLachlan, A

subjects: Environment

abstract: This hypotheses article presents understandings and practices of tohu (signs) in the personal, eco-environmental, and spiritual wellbeing of Māori. Tohu can be observed in the natural, social, physical, or spiritual environment, and within a Māori worldview provide important ways of understanding and responding to phenomena. Wānanga (shared dialogue and debate) were held with seven Māori clinical psychologists from He Paiaka Tōtara (Māori Psychologist Network) and two mātauranga Māori specialists to explore their experiences, knowledge, and perspectives about tohu, with their insights collected through online information sharing. Our wānanga goals were to inform the creation of a therapeutic framework to address patu ngākau, psychological and spiritual trauma experienced by Māori. The results identified that tohu are located within the person and their environment, and the importance of exploring how tohu are interpreted. We propose a TOHU acronym as a framework for understanding and addressing the multifaceted impacts of patu ngākau.

text: The TOHU framework: Sensing and interpreting tohu to heal from trauma This hypotheses article presents understandings and practices of tohu (signs) in the personal, eco-environmental, and spiritual wellbeing of Māori. Tohu can be observed in the natural, social, physical, or spiritual environment, and within a Māori worldview provide important ways of understanding and responding to phenomena. Wānanga (shared dialogue and debate) were held with seven Māori clinical psychologists from He Paiaka Tōtara (Māori Psychologist Network) and two mātauranga Māori specialists to explore their experiences, knowledge, and perspectives about tohu, with their insights collected through online information sharing. Our wānanga goals were to inform the creation of a therapeutic framework to address patu ngākau, psychological and spiritual trauma experienced by Māori. The results identified that tohu are located within the person and their environment, and the importance of exploring how tohu are interpreted. We propose a TOHU acronym as a framework for understanding and addressing the multifaceted impacts of patu ngākau.

year: 2024