# `Text.Language.Classifier.Fasttext.Detection`
[🔗](https://github.com/kipcole9/text/blob/v0.5.0/lib/language/classifier/fasttext/detection.ex#L1)

The result of running fastText language identification on a piece of
text.

### Fields

* `language` is the BCP-47 language subtag fastText reports — typically
  a two-letter ISO 639-1 code (`"en"`, `"fr"`, `"zh"`), occasionally
  three-letter ISO 639-3 (`"als"`, `"yue"`).

* `confidence` is the probability fastText assigns to the top-1 label,
  in `[0.0, 1.0]`.

* `script` is the dominant Unicode script of the input as detected by
  `Text.Language.Classifier.Fasttext.ScriptDetector`. One of the script
  atoms documented there.

* `alternatives` is the rest of the top-K predictions (excluding the
  top-1), each a `{language, probability}` pair. May be empty when
  `k == 1` was requested.

* `text` is the original input. Kept on the struct so a downstream
  `Text.Language.Classifier.Fasttext.Locale.resolve/2` call can use it
  to disambiguate Hans/Hant or other script-derived locale information.

# `alternative`

```elixir
@type alternative() :: {String.t(), float()}
```

# `t`

```elixir
@type t() :: %Text.Language.Classifier.Fasttext.Detection{
  alternatives: [alternative()],
  confidence: float(),
  language: String.t(),
  script: Text.Language.Classifier.Fasttext.ScriptDetector.script(),
  text: String.t()
}
```

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*Consult [api-reference.md](api-reference.md) for complete listing*