Benchmarking Machine Learning Algorithms on Blood Glucose Prediction for Type I Diabetes in Comparison With Classical Time-Series Models

2020 ◽  
Vol 67 (11) ◽  
pp. 3101-3124 ◽  
Author(s):  
Jinyu Xie ◽  
Qian Wang
Keyword(s):  
Machine Learning ◽  
Time Series ◽  
Blood Glucose ◽  
Type I Diabetes ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Time Series Models ◽  
Type I ◽  
Glucose Prediction

Jump detection in financial time series using machine learning algorithms

2019 ◽  
Vol 24 (3) ◽  
pp. 1789-1801 ◽  
Author(s):  
Jay F. K. Au Yeung ◽  
Zi-kai Wei ◽  
Kit Yan Chan ◽  
Henry Y. K. Lau ◽  
Ka-Fai Cedric Yiu
Keyword(s):  
Machine Learning ◽  
Time Series ◽  
Financial Time Series ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Jump Detection ◽  
Financial Time

scholarly journals Rainfall prediction: A comparative analysis of modern machine learning algorithms for time-series forecasting

2021 ◽  
pp. 100204
Author(s):  
Ari Yair Barrera-Animas ◽  
Lukumon Oladayo Oyedele ◽  
Muhammad Bilal ◽  
Taofeek Dolapo Akinosho ◽  
Juan Manuel Davila Delgado ◽  
...  
Keyword(s):  
Machine Learning ◽  
Time Series ◽  
Comparative Analysis ◽  
Learning Algorithms ◽  
Time Series Forecasting ◽  
Machine Learning Algorithms ◽  
Rainfall Prediction ◽  
Modern Machine

scholarly journals Eagle View: An Abstract Evaluation of Machine Learning Algorithms based on Data Properties

2021 ◽  
Author(s):  
Dhairya Vyas
Keyword(s):  
Machine Learning ◽  
Time Series ◽  
Time Series Data ◽  
Learning Algorithms ◽  
Numerical Data ◽  
Machine Learning Algorithms ◽  
Series Data ◽  
Learning Methods ◽  
Machine Learning Methods ◽  
Almost All

In terms of Machine Learning, the majority of the data can be grouped into four categories: numerical data, category data, time-series data, and text. We use different classifiers for different data properties, such as the Supervised; Unsupervised; and Reinforcement. Each Categorises has classifier we have tested almost all machine learning methods and make analysis among them.

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