🍀 Challenge: Classification Using IRIS DataSet
Explore how to apply a simple perceptron model to classify the IRIS dataset by preprocessing data with pandas, managing NumPy arrays, and optimizing weights for accurate predictions.
We'll cover the following...
We'll cover the following...
Problem statement
The IRIS data set is taken from the UCI repository of datasets. It has four features and a label that classifies the flower.
| sepal_length | sepal_width | petal_length | petal_width | species |
|---|---|---|---|---|
| 6.7 | 3.3 | 5.7 | 2.1 | Iris-setosa |
| 6.4 | 3.1 | 5.5 | 1.8 | Iris-setosa |
| 4.9 | 3.1 | 1.5 | 0.1 | Iris-virginca |
| 5.5 | 3.5 | 1.3 | 0.2 | Iris-virginca |
The flowers can belong to either of the following classes:
Find the optimal weights that can classify each flower: Iris-setosa and non-iris setosa.
The data is ...