When you start scikit-multiflow container with jupyter, you will find a Quick Start jupyter notebook.
Quick Start
For the scikit-multiflow container with python. There are two Hello World examples.
In hoeffding_tree.py, data is generated from WaveformGenerator.
hoeffding_tree.py
WaveformGenerator
In ht_from_file.py, data is generated from a csv file elec.csv.
ht_from_file.py
elec.csv
Start scikit-multiflow Docker container
$ docker run -it skmultiflow/scikit-multiflow:latest
Run the Hoeffding Tree example :
$ python hoeffding_tree.py
It is possible to write and edit your code on your local machine and run it in the container.
First, create a work directory.
$ mkdir workdir
Second, you get the path of that directory. This will be the value of hostDir
hostDir
$ cd workdir && pwd
In this example, let’s assume that this command returns the following path : /tmp/workdir
/tmp/workdir
Next, you mount the directory with the following command and start scikit-multiflow container
$ docker run -it -v /tmp/workdir:/app --shm-size 2G skmultiflow/scikit-multiflow:latest
Let’s download some example to workdir directory. You can also write your own code.
workdir
$ wget https://raw.githubusercontent.com/scikit-multiflow/scikit-multiflow/master/docker/examples/src/hoeffding_tree.py
Now, your files are synchronized with the container. just run it.