Matej Mihelčić's Workflows

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Showing 16 results. Use the filters on the left and the search box below to refine the results.

Workflow Hybrid recommendation system (1)

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This is one hybrid recommendation system combining linear regression recommender, created using RapidMiner core operators, and Recommender extension multiple collaborative filtering and attribute based operators.

Created: 2012-05-17

Credits: User Matej Mihelčić User Matko Bošnjak

Workflow Parameter optimization (1)

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This is a parameter optimization workflow for rating prediction recommendation operators.

Created: 2012-02-10 | Last updated: 2012-02-10

Credits: User Matej Mihelčić

Workflow Experimentation through repository access (1)

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This workflow reads train/test dataset from a specified RapidMiner repository and tests selected operator on that datasets. Only datasets specified with a proper regular expression are considered. Train and test data filenames must correspond e.g (train1, test1). Informations about training and testing data, performanse measures of a selected operator are stored as an Excel file. Note: Train/test file names should not be contained in the repository path. E.g training/train is not a god path,...

Created: 2012-01-31 | Last updated: 2012-02-01

Credits: User Matej Mihelčić User Matko Bošnjak User tomS

Workflow Data iteration workflow (RP) (1)

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This is a data iteration workflow used to iterate throug query update sets.

Created: 2012-01-29

Credits: User Matej Mihelčić User Matko Bošnjak

Workflow Model update workflow (RP) (1)

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This is a Model update workflow called from data iteration workflow on every given query set. In the Loop operator model and current training set are retrieved from the repository. Model update is performed on a given query set creating new model. Model and updated train set are saved in the repository.

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

Credits: User Matej Mihelčić

Workflow recommender workflow (RP) (1)

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This is a main online update experimentation workflow. It consists of three Execute Process operators. First operator executes model training workflow. Second operator executes online updates workflow for multiple query update sets. The last operator executes performance testing and comparison workflow. Final performance results are saved in an Excel file.

Created: 2012-01-29

Credits: User Matej Mihelčić

Workflow Model testing workflow (RP) (1)

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This workflow measures performance of three models. Model learned on train data and upgraded using online model updates. Model learned on train data + all query update sets. Model learned on train data only.

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

Credits: User Matej Mihelčić

Workflow Model saving workflow (RP) (1)

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This workflow trains and saves model for a selected rating prediction operator.

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

Credits: User Matej Mihelčić

Workflow Model update workflow (1)

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This is a Model update workflow called from data iteration workflow on every given query set. In the Loop operator model and current training set are retrieved from the repository. Model update is performed on a given query set creating new model. Model and updated train set are saved in the repository.

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

Credits: User Matej Mihelčić User Matko Bošnjak

Workflow Data iteration workflow (1)

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This is a data iteration workflow used to iterate throug query update sets.

Created: 2012-01-29

Credits: User Matej Mihelčić User Matko Bošnjak

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