Develop a Naive bayes model that can predict type of flower based on it's features. The data set contains $3$ classes of $50$ instances each, where each class refers to a type of iris plant. The attribute to be predicted is the class of iris plant. The classes are as follows: $1.$ Iris Setosa, $2.$ Iris Versicolour, $3.$ Iris Virginica

There are $4$ features:

$1.$sepalLength: sepal length in cm

$2.$sepalWidth: sepal width in cm

$3.$petalLength: petal length in cm

$4.$petalWidth: petal width in cm

There are $3$ classes represneting class label of iris flower $\{1,2,3\}$

$1.$Iris Setos

$2.$Iris Versicolour

$3.$Iris Virginica

Part $1$: Visualize the Data

Part $2$: Data Preparation$/$ Data Analysi

Part $3$: Model Training

Part $4$: Evaluate the Model

Part $5$: Improve the Model