title: On ensemble techniques for data stream regression

authors: Gomes, Heitor Murilo

subjects: Science & Technology

abstract: An ensemble of learners tends to exceed the predictive performance of individual learners. This approach has been explored for both batch and online learning. Ensembles methods applied to data stream classification were thoroughly investigated over the years, while their regression counterparts received less attention in comparison. In this work, we discuss and analyze several techniques for generating, aggregating, and updating ensembles of regressors for evolving data streams. We investigate the impact of different strategies for inducing diversity into the ensemble by randomizing the input data (resampling, random subspaces and random patches). On top of that, we devote particular attention to techniques that adapt the ensemble model in response to concept drifts, including adaptive window approaches, fixed periodical resets and randomly determined windows. Extensive empirical experiments show that simple techniques can obtain similar predictive performance to sophisticated algorithms that rely on reactive adaptation (i.e., concept drift detection and recovery).

text: On ensemble techniques for data stream regression An ensemble of learners tends to exceed the predictive performance of individual learners. This approach has been explored for both batch and online learning. Ensembles methods applied to data stream classification were thoroughly investigated over the years, while their regression counterparts received less attention in comparison. In this work, we discuss and analyze several techniques for generating, aggregating, and updating ensembles of regressors for evolving data streams. We investigate the impact of different strategies for inducing diversity into the ensemble by randomizing the input data (resampling, random subspaces and random patches). On top of that, we devote particular attention to techniques that adapt the ensemble model in response to concept drifts, including adaptive window approaches, fixed periodical resets and randomly determined windows. Extensive empirical experiments show that simple techniques can obtain similar predictive performance to sophisticated algorithms that rely on reactive adaptation (i.e., concept drift detection and recovery).

year: 2020

title: Review: The nature of wishing

authors: Cheesman, Sue

subjects: dance

abstract: Review of the dance: The Nature of Wishing.

text: Review: The nature of wishing Review of the dance: The Nature of Wishing.

year: 2006

title: Transitioning from kōhanga reo to kura

authors: Hohepa, Margie Kahukura

abstract: This is a collaborative cross-sector research project involving a kōhanga reo (Māori immersion early childhood language nest) kura (Māori language immersion school) and university-based researchers. It focuses on tamariki (children) moving from kōhanga reo to kura classrooms and will examine the development of an 'akoranga whakawhiti', a transition programme that will be based at Te Kōhanga Reo o Ngā Kuaka in Hamilton. The over arching research question for this project is: Pēhea rā te āhuatanga me te kounga o ngā whakawhitinga mai i te kōhanga ki te kura mō ngā tamariki, whānau, kaiako me te hāpori? - What do effective transitions from kōhanga reo to kura look like, feel like, and sound like, for tamariki, whānau, kaiako and the community? The project aims to provide important new insights into learning and teaching in Māori-medium settings and into ways of enhancing transitions from Maori-medium early childhood education to Māori medium classrooms.

text: Transitioning from kōhanga reo to kura This is a collaborative cross-sector research project involving a kōhanga reo (Māori immersion early childhood language nest) kura (Māori language immersion school) and university-based researchers. It focuses on tamariki (children) moving from kōhanga reo to kura classrooms and will examine the development of an 'akoranga whakawhiti', a transition programme that will be based at Te Kōhanga Reo o Ngā Kuaka in Hamilton. The over arching research question for this project is: Pēhea rā te āhuatanga me te kounga o ngā whakawhitinga mai i te kōhanga ki te kura mō ngā tamariki, whānau, kaiako me te hāpori? - What do effective transitions from kōhanga reo to kura look like, feel like, and sound like, for tamariki, whānau, kaiako and the community? The project aims to provide important new insights into learning and teaching in Māori-medium settings and into ways of enhancing transitions from Maori-medium early childhood education to Māori medium classrooms.

year: 2014