main.py

import seaborn as sns
from sklearn.linear_model import LogisticRegression

# Load iris dataset
iris = sns.load_dataset("iris")

# Prepare features and labels
X = iris.iloc[:, 0:4].values
y = iris.iloc[:, 4].values

# Train logistic regression
modlog = LogisticRegression(max_iter=300)
modlog.fit(X, y)

# Example flower measurements (setosa)
sl = 5.1
sw = 3.5
pl = 1.4
pw = 0.2

# Predict
res = modlog.predict([[sl, sw, pl, pw]])
print("The predicted flower species is " + str(res[0]))