Practising ML: KNIME

Prof. Dr. Mirco Schoenfeld

Motivation

In this course, you shall learn to create your own ML pipeline.

Can you code?

But, I can’t code…!

KNIME

https://www.knime.com/

KNIME

KNIME (/naɪm/), the Konstanz Information Miner,
is a data analytics, reporting and integrating platform.

https://www.knime.com/
https://en.wikipedia.org/wiki/KNIME

Download KNIME

Download KNIME from https://www.knime.com/downloads

Choose either the Latest, or the LTS version.

Download KNIME

You don’t need to register.

Start KNIME

Now, please (install and) start KNIME

Install extensions

Before we can move on, we need to install some extensions.

Install extensions

Install extensions

Install extensions

Dragging the button on the KNIME window starts the installation.

Install extensions

Please install these extensions:

Useful ressources

The KNIME Hub contains many useful resources:

https://hub.knime.com/knime

Advanced usage

Or refer to these articles for advanced examples:

Getting started

Getting started

First, we need some data.

Getting started

We’ll be working with the mouse.csv data from

https://elki-project.github.io/datasets/

Can also be obtained from here

Why mouse, you ask?

Getting started

Getting started

https://elki-project.github.io/tutorial/

Getting started

Getting started

Anyways…

Please .

Getting started

Getting started

Getting started

Getting started

Getting started

Getting started

Getting started

Getting started

Getting started

Getting started

Getting started

Getting started

Getting started

Getting started

Getting started

Getting started

Getting started

It’s your turn

Remove the noise.

  1. Inspect the mouse.csv to find the noise
  2. Design a workflow in KNIME to remove it from the scatter plot.

It’s your turn

How would you remove the noise in or ?

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