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C1 Combined Workflow (1)

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Created: 2010-06-03 | Last updated: 2010-06-03

Credits: Paul Dobson

Association rules as examples (1)

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Uses Groovy scripting to lay out rules and their support metrics as examples.

Created: 2010-06-02

CamelCases (1)

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this process splits up camelcases

Created: 2010-06-02

Creation of New Attribute Depending on Val... (1)

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The process shows the usage of the operator "Generate Attributes" in combination with an "if - then - else" condition and nominal values. The values "value0" and "value1" are mapped to "T1", other values are mapped to "T2" for the new attribute.

Created: 2010-06-01

Linear Regression of Italian bookshops se... (1)

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Someone could help me? Why the correlation between the actual value and the predictive value of the attribute "Quantita" is so low?

Created: 2010-05-28

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Provenance Challenge 1 Workflow in Taverna

Created: 2010-05-28 07:21:42 | Last updated: 2010-06-21 16:15:46

4 items in this pack

Comments: 0 | Viewed: 67 times | Downloaded: 21 times

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Provenance Challenge 1 workflow -- mockup ... (1)

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simulates the image processing for the PC1 workflow using beanshell that simply track test strings an image is a pair (header, image) specified as a list of depth 1: [header,image] so each processor with image input takes an input list. Note that the processors are designed to operate on single images (except softmean that operates on a list of images), but because the initial input is a list of images, all are processed by implicit iteration.

Created: 2010-05-28

Credits: Paolo

Missing value count (1)

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This workflow enables users to filter examples by the number of missing values they contains; it inserts the numeric attribute 'Missings' - representing, for each example, the count of attributes with missing values.

Created: 2010-05-27 | Last updated: 2010-07-13

Plot round results of a backward elimination (1)

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This process will perform a backward elimination and logs all performance and deviation results of each round. This way, you can use the visualizations of rapidminer to asses the performance gain.

Created: 2010-05-26

Simple DPAS query (4)

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queries dpas for each time priode and instrument

Created: 2010-05-26 | Last updated: 2011-12-15

Credits: Anja Le Blanc

Retrieve Instruments for event dates (2)

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Queries the HELIO ICS web service and returns a list of instruments available for the time periodes in VOTable format

Created: 2010-05-26

Credits: Anja Le Blanc

A simple CQL query workflow in caGrid (1)

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1. CQL is a language to query data from caGrid/caBIG services. This workflow is tested with Taverna 2.1.2 and the caGrid Workflow Suite downloadable from http://www.mcs.anl.gov/~wtan/t2/. 2.More information regarding CQL can be found from http://wiki.cagrid.org/display/dataservices. 3. Sample input (95) is provided in the workflow. It is to query all the hybridization data within a microarray experiment whose id is 95.

Created: 2010-05-24 | Last updated: 2010-05-25

Credits: Wei Tan

Query caArray data service and retrieving ... (2)

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need to install Taverna 2 caGrid integration suite from http://www.mcs.anl.gov/~wtan/t2/ and get a cagrid Dorian account (see http://wiki.cagrid.org/display/caGrid13/Home)

Created: 2010-05-24 | Last updated: 2010-05-24

Credits: Wei Tan

simple HEC query (2)

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HEC query for table 'goes_xray_flare'

Created: 2010-05-21 | Last updated: 2010-08-04

Credits: Anja Le Blanc

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ProStack Screencast: Segmentation of Images of Gene ...

Created: 2010-05-20 19:48:40

Credits: Konstantin Kozlov

License: Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 Unported License

File type: AVI video

Comments: 0 | Viewed: 64 times | Downloaded: 26 times

Warp2D - 2D Time Alignment Workflow (3)

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2D Time Alignment We describe a new time alignment method that takes advantage of both dimensions of LC-MS data to resolve ambiguities in peak matching while remaining computationally efficient. This approach, Warp2D, combines peak extraction with a two-dimensional correlation function to provide a reliable alignment scoring function that is insensitive to spurious peaks and background noise. One-dimensional alignment methods are often based on the total-ion-current eluti...

Created: 2010-05-20 | Last updated: 2010-11-22

Credits: Ishtiaq AHMAD

Exclude a Attribute/Variable (1)

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This simple process demonstrates how to exclude a attribute or set of attributes from an example set/data set. In particular the first "Select Attributes" filter excludes the Outlook attribute. The second filter excludes subset {Outlook, Humidity}.

Created: 2010-05-20

Filter Wrong Predicted/Classified Samples (1)

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This process demonstrates how to filter validation samples which are predicted incorrectly. Thee key operator is "Filter Examples" that is set up to "wrong_predictions"

Created: 2010-05-19 | Last updated: 2010-06-08

Apply Same Preprocessing to Learning and V... (1)

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This process demonstrates how to apply the same prepossessing work flow to learning data and test/validation data. Due to overview reasons the preprocessing is hidden in a Preprocessing subprocess. To perform the same preprocessing work flow on the learning and testing data, both are collected to a Collection of Data. Then the "Loop Collection" operator loops over each collection. The actual preprocessing is done inside the "Loop Collection" operator. In the example only a "Rename" is done...

Created: 2010-05-19

Write/Store Correlation Matrix to an Excel... (1)

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This process demonstrates how to write/store/export the correlation matrix of the "Correlation Matrix" operator to an Excel file. One need to generate a Report with the "Generate Report" operator and export the Report to an Excel file.

Created: 2010-05-19

OpenTox Handle Task (8)

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Waits for a task to be finished and returns resulting URI

Created: 2010-05-18

Discard Attribute with More than x% Missin... (1)

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This process loops over all attributes and calculates the fraction of missings for each attribute. If this fration is larger than the fraction defined in the first "Set Macro" operator (macro: max_unknown), the attribute will be removed from the example set.

Created: 2010-05-15

Convert Nominal to Binominal to Numerical (1)

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This is a standard preprocessing subprocess taking nominal (categorical) attributes and introduces binominal dummy attributes before those are transformed to numerical which can be then used by learning schemes like SVM or Logistic Regression.

Created: 2010-05-15

Pivoting (1)

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This process shows the basics of Pivoting. A data set with three columns is loaded and partially generated. Afterwards, the data is rotated and missings are replaced by zero.

Created: 2010-05-15

Evaluating Multiple Models with Looped X-V... (1)

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This process shows how multiple different models can be evaluated with cross validation runs. This allows for the comparison of, for example, three prediction model types (e.g., ANN, SVM and DT) all at once under a x-fold cross validation. Having said that, the process actually performs the same cross validation several times using each time a different modeling scheme. It makes use of loops, collections, subprocess selection and macros and is therefore also an interesting showcase for more ...

Created: 2010-05-15