This page (revision-31) was last changed on 13-Sep-2022 16:14 by Dan Hudson

This page was created on 22-Mar-2022 15:18 by Dan Hudson

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Exploratory Pattern Analytics
Exploratory Pattern Analytics

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At line 23 changed one line
- Link to the guideline:
- Link to the guideline:
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.
At line 31 changed one line
e.g. got the the gitup [[link], copythe code into [[XY] and start using
The tool is available through the Data Analytics tool interface at: [https://github.com/cslab-hub/Data_Analytics_DIPLAST/tree/epa]. Installation instructions are included in the file named "Installation.docx". The python interface for programmers is available at: [https://github.com/cslab-hub/sd4py].
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__%%( color: #003399; font-size: 18px; )Use case/problem:/%__ Selecting material (recyclate) for specificproduct requirements
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[[General] + [[Tool-specific]
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.
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__%%( color: #003399; font-size: 18px; )Contact person of the tool: /%__Dan Hudson
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__%%( color: #003399; font-size: 18px; )Contact person of the tool: /%__Stefan Bloemheuvel
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! Tool Description
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.
At line 62 removed 12 lines
! Guidelines
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.
! Getting Started
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].
 
 
This page (revision-31) was last changed on 13-Sep-2022 16:14 by Dan HudsonTop