Explore Overfit through 2 example sentences from English, with an explanation of the meaning. Ideal for language learners, writers and word enthusiasts.
Overfit meaning
To use a statistical model that has too many parameters relative to the size of the sample, leading to a good fit with the sample data but a poor fit with new data.
Using Overfit
- The main meaning on this page is: To use a statistical model that has too many parameters relative to the size of the sample, leading to a good fit with the sample data but a poor fit with new data.
Context around Overfit
- Average sentence length in these examples: 25.5 words
- Position in the sentence: 1 start, 0 middle, 1 end
- Sentence types: 2 statements, 0 questions, 0 exclamations
Corpus analysis for Overfit
- In this selection, "overfit" usually appears near the start of the sentence. The average example has 25.5 words, and this corpus slice is mostly made up of statements.
- Recognizable usage signals include to be overfit to narrow and you can overfit even when. That gives this page its own corpus information beyond isolated example sentences.
- By corpus frequency, "overfit" sits close to words such as aabb, aabria and aacha, which helps place it inside the broader word index.
Example types with overfit
The same corpus examples are grouped by length and sentence type, making it easier to see the contexts in which the word appears:
Some systems may perform well on a benchmark like Stanford’s SQuAD question and answering test, but appear to be overfit to narrow tasks. (24 words)
You can overfit even when there are no measurement errors (stochastic noise) if the function you are trying to learn is too complex for your learning model. (27 words)
You can overfit even when there are no measurement errors (stochastic noise) if the function you are trying to learn is too complex for your learning model. (27 words)
Some systems may perform well on a benchmark like Stanford’s SQuAD question and answering test, but appear to be overfit to narrow tasks. (24 words)
Example sentences (2)
Some systems may perform well on a benchmark like Stanford’s SQuAD question and answering test, but appear to be overfit to narrow tasks.
You can overfit even when there are no measurement errors (stochastic noise) if the function you are trying to learn is too complex for your learning model.