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Sklearn Basics 4: Train a Coclustering
======================================
The steps to train a coclustering model with Khiops are very similar to
what we have already seen in the basic classifier tutorials.
We start by importing the sklearn estimator ``KhiopsCoclustering`` and
defining a helper function:
.. code:: ipython3
import os
import platform
import subprocess
import pandas as pd
from khiops import core as kh
from khiops.sklearn import KhiopsCoclustering
# If there are any issues you may Khiops status with the following command
# kh.get_runner().print_status()
For this tutorial, we use the dataset ``CountriesByOrganization`` that
contains the relation country-organization for a large number of
countries and organizations (*it is bit outdated though*). The objective
is to build a coclustering between Country and Organization and see
which countries resemble the most in terms of organizations.
Let’s first load this dataset and check its content:
.. code:: ipython3
countries_data_file = os.path.join(
"data", "CountriesByOrganization", "CountriesByOrganization.csv"
)
X_countries = pd.read_csv(countries_data_file, sep=";")
print("CountriesByOrganization dataset:")
display(X_countries)
.. parsed-literal::
CountriesByOrganization dataset:
.. parsed-literal::
Country Organization
0 Afghanistan AsDB
1 Afghanistan COLOMBO
2 Afghanistan ECO
3 Afghanistan ICCROM
4 Afghanistan NAM
... ... ...
11187 Zimbabwe WHO
11188 Zimbabwe WIPO
11189 Zimbabwe WMO
11190 Zimbabwe WTO
11191 Zimbabwe WTOURO
[11192 rows x 2 columns]
Now, let’s build the coclustering model.
Note that a coclustering model is learned in an unsupervised way and
aims to cluster jointly rows and columns of a matrix. So we need to
provide a column name to be able to deploy it on a specific column. We
do this by setting the ``fit`` parameter ``id_column``:
.. code:: ipython3
khcc_countries = KhiopsCoclustering()
khcc_countries.fit(X_countries, id_column="Country")
.. raw:: html
KhiopsCoclustering()
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
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In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.