Search results for "rapidminer"

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

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

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

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

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

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

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

Combining nominal attributes with missing (1)

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This process will show how one can combine nominal values of attributes that contain missing values. A generate attribute operator is used and hence forbidden characters must first be replaced. After this, a condition in the generation ensures that no question mark (standing for missing value) will be shown in the result, if any of the two combined attributes is known.

Created: 2010-06-04

Prepending common prefix to attributes (1)

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This process shows how one can add a common prefix to a subset of attributes. First a subset might be defined by the attribute set selection parameters of the rename by replacing operator. Then one can make use of the capturing group functionality of regular expressions to insert the original name into the replacement.

Created: 2010-06-04

Transform Attribute Names to Upper Case (S... (1)

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This process uses a Script operator which transforms the attribute names of the input example set into UPPER case.

Created: 2010-06-06