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ML with IRIS data set using Incorta

This article shows how to use a classification Machine Learning (ML) algorithm on the Iris Flower data set. It first creates a model based on a training data set and then scores the the test data set and gives the prediction of the flower based on the model.

  • Install the following python libraries on the Incorta server using pip install if they are not installed.

pandas

numpy

matplotlib

seaborn

scikit-learn

  • Import the schema zip from schema page and the data file from the UI .  The Iris ML schema has two examples, one using pandas and other using incorta_ML .
  • Load the IrisData table
  • Now open the materialized views in a notebook and start running each of the paragraphs to see what it does.

 

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