Documentation » Historique » Version 15
François Rioult, 18/07/2010 17:45
1 | 3 | François Rioult | h1. Documentation |
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2 | 1 | François Rioult | |
3 | 4 | François Rioult | KDAriane is a set of operators for data mining and machine learning, and a set of scenarios (supervised classification, missing values completion, strong emerging pattern mining, etc.). It uses Ariane as a graphical platform for designing the data streams. |
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5 | 1 | François Rioult | h2. Installation |
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7 | 13 | François Rioult | * [[Prerequisite]] |
8 | 4 | François Rioult | * [[KDAriane]] |
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10 | 5 | François Rioult | h2. Special operators for shell scripting |
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12 | 5 | François Rioult | KDAriane is provided with basic components for executing shell scripts. The choice depends on how many parameters (p), input (i) and output (o) you want. The operators are named |
13 | @"eval" + p + i + o @ and call the eponymous .sh script. |
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15 | 6 | François Rioult | When an operator is executed, Ariane launches the script (for example @script.sh@) associated to the operator with giving the following arguments: |
16 | <pre> |
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17 | script.sh parameter-1 parameter-2 ... parameter-p input-1 input-2 ... input-i output-1 output-2 ... output-o |
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18 | </pre> |
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20 | In Ariane, every operator has a return value, even if it has no output. |
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22 | 9 | François Rioult | The operator are divided in two categories: |
23 | 14 | François Rioult | * [[KDD operators]] are special components for calling Weka components or RapidMiner processes. |
24 | 9 | François Rioult | * [[Shell operators]] that directly execute the commands entered by Ariane. |
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26 | 15 | François Rioult | h2. Pattern mining prototypes |
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28 | * [[music-dfs]] |
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31 | 1 | François Rioult | h2. Scenarios |
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33 | KDAriane provides some examples of KDD realized through Ariane: |
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34 | 11 | François Rioult | * [[Data preparation]] : a first scenario for the binarization of CSV data. |
35 | 10 | François Rioult | * pattern mining and complexity visualization |
36 | * supervised classification with association rules |
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37 | * experiences about perturbation on training and test file with Weka classifiers and RapidMiner processes. |