myExperiment - Search

Creator

Lawrynka

View

Download

RMonto pack

Created: 2012-01-29 09:47:09 | Last updated: 2012-03-05 22:24:02

RMonto is an ontological extension to RapidMiner, that provides possibility of machine learning with formal ontologies. RMonto is an easily extendable framework, currently providing support for unsupervised clustering with kernel methods and (frequent) pattern mining in knowledge bases. One important feature of RMonto is that it enables working directly on structured, relational data. Additionally, its custom algorithm implementations may be combined with the power of RapidMiner thr...

9 items in this pack

Comments: 0 | Viewed: 135 times | Downloaded: 31 times

This Pack has no tags!

Creator

Simon Fischer

View

Download

Sudoku solving with RapidMiner (Who Wants to be a Da...

Created: 2012-09-04 16:56:44 | Last updated: 2012-09-04 16:58:26

A fun event at the annual RapidMiner conference RCOMM is the live data mining challenge "Who wants to be a data miner?" where contestants solve tasks data analysis tasks within a few minutes. In 2012 the task was to (partially) solve a Sudoku puzzle. Processes 1 to 3 in this pack correspond to the three tasks whereas process 0 loads the initial data and task 4 is a bonus process that solves the entire Sudoku. Make sure the processes are saved under the name they have on myExperimen...

5 items in this pack

Comments: 0 | Viewed: 111 times | Downloaded: 78 times

Tags:

Creator

Jedrzej Potoniec

View

Download

RapidMiner workflows for paper "Pattern based featur...

Created: 2013-04-16 08:00:13 | Last updated: 2013-05-15 21:12:19

No description

15 items in this pack

Comments: 0 | Viewed: 55 times | Downloaded: 43 times

This Pack has no tags!

RapidMiner

Uploader

mansoor khan

Mining Semantic Web data using FastMap - E... (1)

Download

This workflow describes how to learn from the Semantic Web's data. The input to the workflow is a feature vector developed from a RDF resource. The loaded example set is then divided into training and test parts. These sub-example sets are used by the FastMap operators (encapsulate the FastMap data transformation technique), which processes each feature at a time and transform the data into a different space. This transformed data is more meaningful and helps the learner to improve classfica...

Created: 2011-06-25 | Last updated: 2011-06-25

RapidMiner

Uploader

mansoor khan

Mining Semantic Web data using FastMap - R... (1)

Download

This workflow will explain that how an example set can be extracted from an RDF resource using the provided SPARQL query. This example set is then divided into training and test parts. These sub-example sets are used by the FastMap operators (encapsulate the FastMap data transformation technique), which processes each feature at a time and transform the data into a different space. This transformed data is more meaningful and helps the learner to improve classfication peformance. The tranfo...

Created: 2011-06-25 | Last updated: 2011-06-25

RapidMiner

Uploader

mansoor khan

Mining Semantic Web data using Corresponde... (1)

Download

This workflow will explain that how an example set can be extracted from an RDF resource using the provided SPARQL query. This example set is then divided into training and test parts. These sub-example sets are used by the Correspondencce Analysis operators (encapsulate the Correspondencce Analysis data transformation technique) which processes each feature at a time and transform the data into a different space. This transformed data is more meaningful and helps the learner to improve clas...

Created: 2011-06-25 | Last updated: 2011-06-25

RapidMiner

Uploader

Simon Fischer

Transaction Analysis Demo from RM 5 Intro Day (1)

Download

This is the demo process presented at the RapidMiner 5 Intro Day. It combines customer segmentation with direct mailing. It loads some transaction data, aggregates and pivotes the data so it can be used by a clustering to perform a customer segmentation. Then, additional data is joined with the clustered data. First, response/no-response data is joined, and them some additional information about the users is added. Finally, customers are classified into response/no-response classes. The dat...

Created: 2010-04-30 | Last updated: 2010-05-05

RapidMiner

Uploader

mansoor khan

Mining Semantic Web data using Corresponde... (1)

Download

This workflow describes how to learn from the Semantic Web's data using a data transformation algorithm 'Correspondence Analysis'. The input to the workflow is a feature vector developed from a RDF resource. The loaded example set is divided into training and test parts. These sub-example sets are used by the Correspondence Analysis operators (encapsulate the Correspondence Analysis data transformation technique) which processes each feature at a time and transform the data into a different...