Workflows

Finding all Examples that have duplicate v... (1)

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This process will retrieve all examples, who have identical values in a specific attribute. For testing, the following data can be writen into the file, that will be read by the Read CSV operator: CID,Value 3596,X 4054,X 4054,X 3000,S 3000,T 3000,U 32135,S The target of this process is to return the two examples having the same value in the CID column. To achieve this, first a real id is generated by the generate id. After this, we have to find all duplicates: For this we first remove dupl...

Created: 2010-06-18

Discretization into Deviation Interval aro... (1)

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This process shows how numerical attributes can be discretized into intervals based on the standard deviation for each attribute around their mean values.

Created: 2010-06-22 | Last updated: 2010-06-22

Pre process data per group using recall re... (1)

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This process takes as input a dataset with different groups. For each group it discretises attributes into High, Medium, Low. This creates a group invariant representation.

Created: 2010-06-23 | Last updated: 2010-06-23

Macro Propagation into Subprocesses and Ex... (1)

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<p> This small process demonstrates how to propagate macros into a subprocess or Execute Process operator </p> <p> When macros are set once, they are available in subprocesses imediatly (see Generate Attributes in the seconde Subprocess operator) </p> <p> If someone wants to propagate a macro into a Excecute Process operator one need to edit the "macros" parameter in the Parameters list of the Execute Process operator. </p> Tags: Subprocess, Execute Proc...

Created: 2010-06-25

Holograph Reduced Representation (1)

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After Kanerwa

Created: 2010-06-29

Generating Example Weights depending on label (1)

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This process uses a Generate Attribute operator for assigning new weights to examples. It uses the if condition of this operator to distinguish between labels. This can be especially useful if you have a strong bias in your class frequency, which can harm learning. Please note that you must use a learning algorithm that supports weighted examples.

Created: 2010-05-03

Weighted Score Tables (1)

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This process calculates a weighted score as known from SAP BW. The first operator generates data similar to that used in the links you provided. The next operator (Discretize) defines the different age groups. The next three operators map each age group to the value used for scoring. The last operator finally calculates the score and adds it as a new column to your data set.

Created: 2010-05-05

Simple Recommender System Web Service (1)

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 This workflow takes macro value of user request and computes top-n recommendations from already learned model on train set. Macro value is transformed to example set with the appropriate \textit{user identification} role within \textit{ProcessInput} subprocess operator.   Simple recommendation web service workflow takes three inputs: \begin{enumerate} \item Macro value \textit{user} - identification number of user request \item Train set from RM repository \item Learned Mo...

Created: 2012-05-10 | Last updated: 2012-05-10

Calibration for execution time extension (1)

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 Benchmark workflow that loops Naive Bayes operator many times and provides estimate of the system's overall performance.

Created: 2012-05-10 | Last updated: 2012-05-10

Front-end Recommendation Web Service (1)

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 Front-end recommendation web service has a simple job to query the cached recommendations from the \textit{item recommendation table}

Created: 2012-05-11 | Last updated: 2012-05-11