Write a computer program that trains a series of perceptrons, based on PLA, to classify iris data
- Features/Attributes: Sepal length, Sepal width, Patel length, Patel width
- Class labels/Species: Versicolor, Setosa, Virginica
- The Iris dataset includes three iris species, Versicolor, Setosa and Virginica, with 50 samples each, where each sample is represented by four features, Petal_Length (in cm), Petal_Width (in cm), Sepal_Length (in cm) and Sepal_Width (in cm), for an Iris flower.
Iris data: https://raw.githubusercontent.com/mwaskom/seaborn-data/master/iris.csv
data set preview:
| XXX | sepal_length | sepal_width | petal_length | petal_width | species |
|---|---|---|---|---|---|
| 0 | 5.1 | 3.5 | 1.4 | 0.2 | setosa |
| 1 | 4.9 | 3.0 | 1.4 | 0.2 | setosa |
| 2 | 4.7 | 3.2 | 1.3 | 0.2 | setosa |
| 3 | 4.6 | 3.1 | 1.5 | 0.2 | setosa |
| 4 | 5.0 | 3.6 | 1.4 | 0.2 | setosa |
| 5 | 5.4 | 3.9 | 1.7 | 0.4 | setosa |
| 6 | 4.6 | 3.4 | 1.4 | 0.3 | setosa |
| 7 | 5.0 | 3.4 | 1.5 | 0.2 | setosa |
| 8 | 4.4 | 2.9 | 1.4 | 0.2 | setosa |
| 9 | 4.9 | 3.1 | 1.5 | 0.1 | setosa |
final result:
