Have you ever noticed the little panel, named "KNIME Example Flow Server", at the bottom right of the KNIME workbench? Even if you do not have a KNIME server, connecting to the public KNIME server might be useful.
This panel connects to the KNIME public server, which is a KNIME Server with restricted access. To connect to the KNIME public server just click the "Connect" button (of course you need to have Internet connection).
This panel connects to the KNIME public server, which is a KNIME Server with restricted access. To connect to the KNIME public server just click the "Connect" button (of course you need to have Internet connection).
Once the connection to the public server has been established, a list of workflow groups appears in the "KNIME Example Flow Server" panel. Now you cannot upload or run any of the workflows on the KNIME public server, but you can download them to your own workspace. These are all example workflows, grouped by topic, and represent an easy way to learn how to use some particular nodes or how tio implement the solutions for specific applications.
To download a workflow, just right-click the workflow and select "Download Workflow". Thus the selected workflow will appear in the list of workflow projects in the current workspace. The workflow has been downloaded from the server comprehensive of its input data.
To download a workflow, just right-click the workflow and select "Download Workflow". Thus the selected workflow will appear in the list of workflow projects in the current workspace. The workflow has been downloaded from the server comprehensive of its input data.
There are many areas (i.e. the workflow groups) of examples listed in the "KNIME Example Flow Server" panel. In particular, I recommend having a look at the "002_DataMining" and at the "050_Applications" workflow groups.
"002_DataMining" contains examples on how to train and apply data mining models, be it a decision tree or a neural network. "050_Applications" contains example solutions for the most common problems in data mining, like how to implement a recommandation engine or how to perform a credit scoring on your data.
"002_DataMining" contains examples on how to train and apply data mining models, be it a decision tree or a neural network. "050_Applications" contains example solutions for the most common problems in data mining, like how to implement a recommandation engine or how to perform a credit scoring on your data.
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