To find the answer to our question, we will consider the famous iris flower dataset as an example dataset. The following image is of iris versicolor species. To identify the species, we need some more information other than just an image of the species, such as the flower's Petal length, Petal width, Sepal length, and Sepal width would help us identify the image better:
The dataset not only contains examples of versicolor but also contains examples of setosa and virginica as well. Every example in the dataset contains these four measurements. The dataset contains around 150 examples, with 50 examples of each species. We can use a decision tree or any other model to predict the species of a new flower, if provided with the same four measurements. As we know same species will have almost similar measurements. Since similarity has different definition all together but here we consider similarity as the closeness on a graph, if we consider each point is a flower. The following...