Icon

Asst 3 Q6

Q6. Some of the analytics techniques are only able to work with numeric(quantitative) attributes. In order to use the information carried by qualitative attributeswith such techniques, we need to convert string attributes into numeric. To this end,we can convert each nominal (string) attribute with n levels to n numeric binaryattributes, one for each level. Using a “One to Many” node in KNIME convert the stringattribute “view” to multiple binary attributes. How many new attributes were created? A: 14 new attributes were created from the waterfront, view, condition, and renovatedattributes DatasetFilter numeric string datadata reviewInput for missing values File Reader One to Many Statistics Missing Value Q6. Some of the analytics techniques are only able to work with numeric(quantitative) attributes. In order to use the information carried by qualitative attributeswith such techniques, we need to convert string attributes into numeric. To this end,we can convert each nominal (string) attribute with n levels to n numeric binaryattributes, one for each level. Using a “One to Many” node in KNIME convert the stringattribute “view” to multiple binary attributes. How many new attributes were created? A: 14 new attributes were created from the waterfront, view, condition, and renovatedattributes DatasetFilter numeric string datadata reviewInput for missing valuesFile Reader One to Many Statistics Missing Value

Nodes

Extensions

Links

Download

To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: Pelican
Created at: 2021-09-26
On NodePit since: 2021-10-19
Last update: 2024-04-27
Created with KNIME version: v4.4.1

Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.

Try NodePit Runner!