Definition

Describing a situation where a model is too closely fitted to a specific set of data, resulting in poor performance on new data.

Example

The model was overfit, making it unable to generalize to unseen examples.

Conversation

Did you see the river after the last storm?

Yeah, it looked so different! It seemed to have overfit the landscape.

I know, right? It’s strange how nature can reshape itself like that.

Exactly! It makes you appreciate the power of water.

Synonyms & Antonyms

Definition

A situation in which a model is too closely tailored to a specific set of data, resulting in poor performance on new data.

Example

The model's tendency to overfit the training data led to inaccurate predictions on the test set.

Conversation

I read about this concept called overfit in my statistics class.

Oh really? What does that mean exactly?

It refers to when a model matches the training data too closely, like it can't generalize well.

Definition

To create a statistical model that is too complex for the amount of data available, resulting in a model that works well with the training data but poorly with new, unseen data.

Example

If you overfit your model, it may perform poorly on test data despite being accurate on the training set.

Tense Forms

Conversation

I was reading about machine learning, and they say you can easily overfit your model if you're not careful.

Yeah, I heard that too. It makes sense because too many features can confuse the model.

Root Explanation

Overfit → It is formed from "over-" (meaning excessively) and "fit" (from Old English "fitten", meaning to make suitable or to adapt). The word "overfit" means to excessively adapt a model to a specific set of data, often leading to poor generalization.

Memory Tip

Think of 'over' meaning excessively and 'fit' meaning to adapt — this helps you remember that overfit means to adapt too much to specific data.

Visually Confused Words