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Page References

Incoming links Outgoing links
Exploratory Pattern Analytics
Exploratory Pattern Analytics

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Difference between version and

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(Please insert an screenshot of the Tool)
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__%%( color: #003399; font-size: 18px;)Type of tool:__ e.g. web application or desktop application
(Please insert an screenshot of the Tool)[http://][Exploratory Pattern Analytics]
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__%%( color: #003399; font-size: 18px;)Required skills: __
__%%( color: #003399; font-size: 18px; )Type of tool:/%__ e.g. web application or desktop application
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__%%( color: #003399; font-size: 18px; )Required skills: /%__
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__%%( color: #003399; font-size: 18px;)Short description of the tool: __
__%%( color: #003399; font-size: 18px; )Short description of the tool: /%__
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- Detailed description: Link to the guideline:
- Detailed description: Link to the guideline:
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__%%( color: #003399; font-size: 18px;)Disclaimer:__
__%%( color: #003399; font-size: 18px; )Disclaimer:/%__
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__%%( color: #003399; font-size: 18px;)How to use/download/access it:__
__%%( color: #003399; font-size: 18px; )How to use/download/access it:/%__
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e.g. got the the gitup [[link], copy
the code into [[XY] and start using\\
e.g. got the the gitup [[link], copythe code into [[XY] and start using
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__%%( color: #003399; font-size: 18px;)Use case/problem:__ Selecting material (recyclate) for specific
product requirements
__%%( color: #003399; font-size: 18px; )Use case/problem:/%__ Selecting material (recyclate) for specificproduct requirements
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__%%( color: #003399; font-size: 18px;)Description of the problem the tools solves:__
__%%( color: #003399; font-size: 18px; )Description of the problem the tools solves:/%__
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__%%( color: #003399; font-size: 18px;)Contact person of the tool: __
Stefan Bloemheuvel
__%%( color: #003399; font-size: 18px; )Contact person of the tool: /%__Stefan Bloemheuvel
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__%%( color: #003399; font-size: 18px;)Related tools:__
__%%( color: #003399; font-size: 18px; )Related tools:/%__
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!Tool Description
! Tool Description
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An important step in data analysis is data exploration, to achieve a better
understanding of the data. The Exploratory Pattern Analytics (EPA)
tool works on prepared/preprocessed tabular data. It provides
explanatory patterns, i.e., simple rules between some parameters
(e.g., temperature, pressure) that are predictive for a certain
target parameter (e.g., scrap rate). This provides important insights
enhancing data understanding.
For example, it could be used to better understand why certain known outliers occur
in process data.
An important step in data analysis is data exploration, to achieve a betterunderstanding of the data. The Exploratory Pattern Analytics (EPA)tool works on prepared/preprocessed tabular data. It providesexplanatory patterns, i.e., simple rules between some parameters(e.g., temperature, pressure) that are predictive for a certaintarget parameter (e.g., scrap rate). This provides important insightsenhancing data understanding.For example, it could be used to better understand why certain known outliers occurin process data.
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!Guidelines
! Guidelines
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Before you get started, take a look at the [guidelines |Exploratory Pattern Analytics/Paper mill EPA tool example updated.odt] and make yourself familiar with how to use the tool.
Before you get started, take a look at the [guidelines|Paper mill EPA tool example updated.odt] and make yourself familiar with how to use the tool.
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!Getting Started
! Getting Started
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The tool is available through the Data Analytics tool interface at: [https://github.com/cslab-hub/Data_Analytics_DIPLAST/tree/epa]. The python interface for programmers is available at: [https://github.com/cslab-hub/sd4py].
The tool is available through the Data Analytics tool interface at: [https://github.com/cslab-hub/Data_Analytics_DIPLAST/tree/epa]. The python interface for programmers is available at: [https://github.com/cslab-hub/sd4py].
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This page (revision-31) was last changed on 13-Sep-2022 16:14 by Dan HudsonTop