myExperiment - Content

RapidMiner

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Simon Fischer

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This is an image mining process using the image mining Web service provided by NHRF within e-Lico. It first uploads a set of images found in a directory, then preprocesses the images and visualizes the result. Furthermore, references to the uploaded images are stored in the local RapidMiner repository so they can later be used for further processing without uploading images a second time.

Created: 2010-04-28 | Last updated: 2012-01-16

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Simon Fischer

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Who Wants to be a Data Miner?

Created: 2011-11-02 17:54:07 | Last updated: 2013-09-09 16:22:11

One of the most fun events at the annual RapidMiner Community Meeting and Conference (RCOMM) is the live data mining process design competition "Who Wants to be a Data Miner?". In this competition, participants must design RapidMiner processes for a given goal within a few minutes. The tasks are related to data mining and data analysis, but are rather uncommon. In fact, most of the challenges ask for things RapidMiner was never supposed to do. This pack contains solutions for these...

12 items in this pack

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Creator

Matko BoÅ¡njak

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e-LICO recommender workflows

Created: 2011-03-15 15:33:48 | Last updated: 2012-01-28 19:39:06

This pack contains recommender system workflows created for the purpose of e-LICO project.

6 items in this pack

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RapidMiner

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Sebastian land

Using Remember / Recall for "tunneling" re... (1)

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This process shows how Remeber and Recall operators can be used for passing results from one position to another position in the process, when it's impossible to make a direct connection. This process introduces another advanced RapidMiner technique: The macro handling. We have used the predefined macro a, accessed by %{a}, that gives the apply count of the operator. So we are remembering each application of the models that are generated in the learning subprocess of the Split validation. Af...

Created: 2010-04-29 | Last updated: 2012-01-16

RapidMiner

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Lawrynka

Loading OWL files (RDF version of videolec... (1)

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The workflow uses RapidMiner extension named RMonto (http://semantic.cs.put.poznan.pl/RMonto/). Operator "Build knowledge base" is responsible for collecting data either from OWL files or SPARQL endpoints or RDF repositories and provide it to the subsequent operators in a workflow. In this workflow it is parametrized in this way, that is builds a Sesame/OWLIM repository from the files specified in "Load file" operators. Paths to OWL files are specified as parameter va...

Created: 2012-01-29 | Last updated: 2012-01-29

RapidMiner

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Lawrynka

Semantic clustering (with alpha-clustering... (1)

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The workflow uses RapidMiner extension named RMonto (http://semantic.cs.put.poznan.pl/RMonto/) to perform clustering of SPARQL query results based on chosen semantic similarity measure. The measure used in this particualr workflow is a kernel that exploits membership of clustered individuals to OWL classes from a background ontology ("Epistemic" kernel from [1]). Since the semantics of the backgound ontology is used in this way, we use the name "semantic clustering". This ...

Created: 2012-01-29 | Last updated: 2012-01-30

RapidMiner

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Lawrynka

Semantic clustering (with AHC) of SPARQL q... (1)

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The workflow uses RapidMiner extension named RMonto (http://semantic.cs.put.poznan.pl/RMonto/) to perform clustering of SPARQL query results based on chosen semantic similarity measure. The measure used in this particualr workflow is a kernel that exploits membership of clustered individuals to OWL classes from a background ontology ("Common classes" kernel from [1]). Since the semantics of the backgound ontology is used in this way, we use the name "semantic clustering". ...

Created: 2012-01-29 | Last updated: 2012-01-29

RapidMiner

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Lawrynka

Semantic clustering (with k-medoids) of SP... (1)

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The workflow uses RapidMiner extension named RMonto (http://semantic.cs.put.poznan.pl/RMonto/) to perform clustering of SPARQL query results based on chosen semantic similarity measure. Since the semantics of the backgound ontology is used in this way, we use the name "semantic clustering". The SPARQL query is entered in a parameter of "SPARQL selector" operator. The clustering operator (k-medoids) allows to specify which of the query variables are to be used as clustering criteria. If more ...

Created: 2012-01-29

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James Eales

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Creating a focused corpus of factual outcomes from b...

Created: 2011-06-28 11:19:04 | Last updated: 2011-12-13 16:02:16

This pack contains resources and supplementary files for the submission to the MIND2011 workshop titled "Creating a focused corpus of factual outcomes from biomedical experiments" by James Eales, George Demetriou and Robert Stevens

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James Eales

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RapidMiner plugin for Taverna videos and descriptions

Created: 2011-06-06 10:17:52 | Last updated: 2011-12-13 16:02:04

This pack contains videos the show how to use various parts of the RapidMiner plugin for Taverna. The videos demonstrate how to build a Taverna workflow which collects a GEO dataset, uploads it to RapidAnalytics, trains a classifier on one half of the data and tests it on the other half. This classification process can be used to gauge how well mutant and control assays agree across experimental repeats.

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