Flower species classification using multi-Layer perceptrons
This is a simple hello world-style program for performing classification using multi-layer perceptrons. For this, we will be using the famous Iris dataset, which can be downloaded from the UCI Machine Learning Repository at https://archive.ics.uci.edu/ml/datasets/Iris. This dataset has four types of datapoints, shown as follows:
Attribute name |
Attribute description |
---|---|
|
Petal length in cm |
|
Petal width in cm |
|
Sepal length in cm |
|
Sepal width in cm |
|
The type of iris flower that is Iris Setosa, Iris Versicolour, Iris Virginica |
This is a simple dataset with three types of Iris classes, as mentioned in the table.
From the perspective of our neural network of perceptrons, we will be using the multi-perceptron algorithm bundled inside the spark ml library and will demonstrate how you can club it with the Spark-provided pipeline API for the easy manipulation of the machine...