Difference between revisions of "ISSS608 2018-19 T1 Assign Hou Xuelin"
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+ | [[Image:Articles-public-mineral-baths-sofia-bulgaria-dreamstime.jpg|left|1200px]] | ||
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+ | <!--MAIN HEADER --> | ||
+ | {|style="background-color:#1B338F;" width="100%" cellspacing="0" cellpadding="0" valign="top" border="0" | | ||
+ | | style="font-family:Century Gothic; font-size:110%; solid #000000; background:#6A5ACD; text-align:center;" width="25%" | | ||
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+ | [[T1_Assign_Hou_Xuelin_Overview| <font color="#FFFFFF">Overview</font>]] | ||
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+ | [[T1_Assign_Hou_Xuelin_Task1| <font color="#FFFFFF">Task1</font>]] | ||
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+ | [[T1_Assign_Hou_Xuelin_Task1| <font color="#FFFFFF">Task2</font>]] | ||
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+ | | style="font-family:Century Gothic; font-size:110%; solid #1B338F; background:#6A5ACD; text-align:center;" width="25%" | | ||
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+ | [[T1_Assign_Hou_Xuelin_Task1| <font color="#FFFFFF">Task3</font>]] | ||
+ | |} | ||
+ | <br/> | ||
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+ | == Background == | ||
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+ | == Motivation == | ||
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+ | == Objectives == | ||
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+ | == Data Source == | ||
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+ | == Methodology == | ||
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+ | ==== Exploratory Analysis ==== | ||
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+ | ==== Explanatory Analysis ==== | ||
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+ | ==== Predictive Analysis ==== | ||
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+ | == Application Libraries & Packages == | ||
+ | {|class="wikitable" | ||
+ | |- | ||
+ | ! Package Name !! Descriptions | ||
+ | |- | ||
+ | | ''TSrepr'' || Methods for representations (i.e. dimensionality reduction, preprocessing, feature extraction) of time series to help more accurate and effective time series data mining. Non-data adaptive, data adaptive, model-based and data dictated (clipped) representation methods are implemented. Also min-max and z-score normalisations, and forecasting accuracy measures are implemented. | ||
+ | |- | ||
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+ | |} | ||
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+ | == References == |
Revision as of 22:18, 28 October 2018
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Contents
Background
Motivation
Objectives
Data Source
Methodology
Exploratory Analysis
Explanatory Analysis
Predictive Analysis
Application Libraries & Packages
Package Name | Descriptions |
---|---|
TSrepr | Methods for representations (i.e. dimensionality reduction, preprocessing, feature extraction) of time series to help more accurate and effective time series data mining. Non-data adaptive, data adaptive, model-based and data dictated (clipped) representation methods are implemented. Also min-max and z-score normalisations, and forecasting accuracy measures are implemented. |