title: SOKNL: A novel way of integrating K-nearest neighbours with adaptive random forest regression for data streams

authors: Sun, Yibin

abstract: Most research in machine learning for data streams has focused on classification algorithms, whereas regression methods have received a lot less attention. This paper proposes Self-Optimising K-Nearest Leaves (SOKNL), a novel forest-based algorithm for streaming regression problems. Specifically, the Adaptive Random Forest Regression, a state-of-the-art online regression algorithm is extended like this: in each leaf, a representative data point – also called centroid – is generated by compressing the information from all instances in that leaf. During the prediction step, instead of letting all trees in the forest participate, the distances between the input instance and all centroids from relevant leaves are calculated, only k trees that possess the smallest distances are utilised for the prediction. Furthermore, we simplify the algorithm by introducing a mechanism for tuning the k values, which is dynamically and automatically optimised based on historical information. This new algorithm produces promising predictive results and achieves a superior ranking according to statistical testing when compared with several standard stream regression methods over typical benchmark datasets. This improvement incurs only a small increase in runtime and memory consumption over the basic Adaptive Random Forest Regressor.

text: SOKNL: A novel way of integrating K-nearest neighbours with adaptive random forest regression for data streams Most research in machine learning for data streams has focused on classification algorithms, whereas regression methods have received a lot less attention. This paper proposes Self-Optimising K-Nearest Leaves (SOKNL), a novel forest-based algorithm for streaming regression problems. Specifically, the Adaptive Random Forest Regression, a state-of-the-art online regression algorithm is extended like this: in each leaf, a representative data point – also called centroid – is generated by compressing the information from all instances in that leaf. During the prediction step, instead of letting all trees in the forest participate, the distances between the input instance and all centroids from relevant leaves are calculated, only k trees that possess the smallest distances are utilised for the prediction. Furthermore, we simplify the algorithm by introducing a mechanism for tuning the k values, which is dynamically and automatically optimised based on historical information. This new algorithm produces promising predictive results and achieves a superior ranking according to statistical testing when compared with several standard stream regression methods over typical benchmark datasets. This improvement incurs only a small increase in runtime and memory consumption over the basic Adaptive Random Forest Regressor.

year: 2022-09-01

title: Linguistics of social media: An introduction to the special issue

authors: Calude, Andreea S.

abstract: It is hard to remember a world without social media (SM). The Internet Relay Chat (IRC) and bulletin boards of the 1980s and the popular early platforms of the 1990s, MySpace, AOL Messenger, and Facebook, gave rise to nothing short of an SM empire in just 50 years. Although we have been considering how language is used on the Internet for some time now, studying the language used on SM is comparatively a newer field of inquiry.

text: Linguistics of social media: An introduction to the special issue It is hard to remember a world without social media (SM). The Internet Relay Chat (IRC) and bulletin boards of the 1980s and the popular early platforms of the 1990s, MySpace, AOL Messenger, and Facebook, gave rise to nothing short of an SM empire in just 50 years. Although we have been considering how language is used on the Internet for some time now, studying the language used on SM is comparatively a newer field of inquiry.

year: 2025

title: Review of Mareikura-Messengers of Io

authors: Crawford, Terri Ripeka

subjects: Mareikura-Messengers of Io

abstract: Review of Tru Paraha's "Mareikura - Messages of Io", Soundings Theatre, Te Papa Tongarewa, Wellington, 6 June 2008.

text: Review of Mareikura-Messengers of Io Review of Tru Paraha's "Mareikura - Messages of Io", Soundings Theatre, Te Papa Tongarewa, Wellington, 6 June 2008.

year: 2009