# fit (0-fit.com)

People say fit to mean something matches or suits a situation. A shirt fits your body. A plan fits the schedule. It means right size, right shape, right moment.

## What a model may hear
- model training (machine learning): start adjusting weights to minimize error on training data
- statistical fitting (statistics and data science): estimate parameters for a distribution or curve to match observed data
- file format (astronomy and GPS): read or write Flexible Image Transport System files, a standard for images and tables
- hardware profile (electronics manufacturing): look up a board configuration or firmware variant by its FIT identifier
- verb for constraint (optimization): treat as a requirement that must be satisfied exactly

## Where people and models part ways
- Says: "This fits my data"
  Means: The explanation matches what I see
  May be taken as: Trigger retraining or parameter estimation on the user's dataset
  Say instead: "This explanation matches my data well"
- Says: "Make it fit"
  Means: Adjust the plan to work within limits
  May be taken as: Invoke curve-fitting or resize an image to fixed dimensions
  Say instead: "Adjust this plan so it stays within these limits"
- Says: "How well does it fit?"
  Means: Is this a good match for my needs?
  May be taken as: Report R-squared, loss values, or statistical goodness-of-fit metrics
  Say instead: "How suitable is this for my situation?"
- Says: "Fit this into the schedule"
  Means: Find a time slot
  May be taken as: Attempt to solve a constraint optimization or bin-packing problem
  Say instead: "Find an available time slot for this"

## Tips
- Say 'suits' or 'matches' when you mean appropriateness, not statistics
- Say 'train the model' instead of 'fit' if you want machine learning
- Add 'statistically' before 'fit' when you want the technical sense
- Specify 'curve' or 'distribution' when asking about statistical fitting
- Avoid 'fit' alone when discussing schedules or plans with code-generating models

## Often confused with
- train: always means machine learning, never clothing size
- match: broader, lacks statistical parameter sense
- suit: social or functional appropriateness, no technical meaning
- adapt: implies change over time, not one-time parameter setting
- optimize: seeks best value, not just agreement with data
- calibrate: adjusts instrument accuracy, not model parameters