Why Underfitting is Like Underfashioning

When a model is underfitted, it's like when you're trying to start a fashion trend with a single, neon-colored, neon-striped, neon-
striped sock on a single foot. It's a bold move, but ultimately, it's a fashion disaster. You look like a clown, and not in a good way.

Imagine you're at the beach, and you're trying to rock a pair of plaid pants with a Hawaiian shirt, a neon pink hat, and a pair of flip flops. It's a clash of styles, just like underfitting. The model is trying to fit the data, but it's like trying to force a fashion trend that just doesn't work.

So, let's avoid underfitting like the plague. It's like trying to start a new fashion trend, but with less clothes.

Go to the Overfitting is Like Overaccessorizing page to learn how overfitting is like accessorizing with too much bling.

		import numpy as np
		from sklearn.linear_model import LogisticRegression

		model = LogisticRegression()
		model.fit(X_train, y_train)

		# Underfitting is like underfashioning, it's a crime!