The Iris dataset from UC-Irvine Machine Learning repository:

• Columns are called input variables or features or attributes.
• The outcome we are trying to predict, is called output variables or targets.
• A row in the table is called training example or instance.
• The whole table is called (training) dataset.
• The problem of predicting is called classification.

The variables are:

• sepal_length: Sepal length, in centimeters, used as input.
• sepal_width: Sepal width, in centimeters, used as input.
• petal_length: Petal length, in centimeters, used as input.
• petal_width: Petal width, in centimeters, used as input.
• class: Iris Setosa, Versicolor, or Virginica, used as the target.