Introduction to Scikit-learn
Chapter 3: Understanding your data
How many categories?
Question 3: How many (and what) categories does the dataset have?
The next thing to find out is - how many categories/classes does this dataset have? And what are these categories/classes? Note that classes here are not related to OOP classes. They just mean categories like “cat” and “dog”.
Luckily, scikit-learn also has that covered with the target_names attribute!
>>> categories = dataset.target_names
>>> print(categories)
['setosa' 'versicolor' 'virginica']
>>> print(len(categories))
3
If done correctly, you should see that the Iris dataset comprises three categories: “setosa”, “versicolor”, and “virginica”.
CC BY-SA 3.0, Link |
By D. Gordon E. Robertson - Own work, CC BY-SA 3.0, Link |
By Eric Hunt - Own work, CC BY-SA 4.0, Link |