Machine Learning Algorithms Explained – Decision Trees
A Decision Tree is a supervised predictive model that can learn to predict discrete or continuous outputs by answering a set of simple questions based on the values of the input features it receives.
To get a better understanding of how DT works, we will use a real-world dataset to better illustrate the concept.
This dataset contains four measurements of three different iris flowers. The measurements are: the sepal length, sepal width, petal length, and petal width. The three types of iris are Setosa, Versicolour, and Virginica, shown below in that order. [Read More]