Titlebook: Data Mining; 16th Australasian Co Rafiqul Islam,Yun‘Sing Koh,Zahidul Islam Conference proceedings 2019 Springer Nature Singapore Pte Ltd. 2

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An Approach to Compress and Represents Time Series Data and Its Application in Electric Power Utilitmbolically which can be used for time series’ classification or anomaly detection. The proposed method is tested using the time series data obtained from utility companies’ substations by comparing the compressed outputs to the original forms. The result is a new discretized set that is lower in vol

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A Hybrid Missing Data Imputation Method for Constructing City Mobility Indicesis paper proposes a new hybrid imputation method to effectively deal with the missing data issue of the Mobility in Cities Database (MCD) to construct city mobility indices. The hybrid method integrates the advantages of decision trees and fuzzy clustering into an iterative algorithm for missing dat

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A Novel Learning-to-Rank Method for Automated Camera Movement Control in E-Sports Spectatinge fans watch tournament games through a camera of the observer. Bigger tournaments hire professional human observers with high-end tools to monitor important events in the game map for broadcasting the game. This setup is prone to errors. It results in missing important events within the game and lo

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Statistical Models of Dengue Feverding conditions of vector mosquitos. We use Hamiltonian Monte Carlo sampling to estimate a seasonal Gaussian process modeling infection rate, and aperiodic basis coefficients for the rate of an “outbreak level” of infection beyond seasonal trends across two separate regions. We use this outbreak lev

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https://doi.org/10.1007/10703260eely-available datasets from the UCI data repository. Results from this testing indicate the two components of SPAARC combined have minimal effect on decision tree classification accuracy yet reduce model build times by as much as 69%.

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