Development build. This page describes main, not a released package. The latest published Lodestar.Text is 0.6.0 — read its documentation.

Home › Text › Vectorization

TfidfVectorizer.Save

Write a fitted vectorizer out, vocabulary and document frequencies together.

public void Save(Stream destination)
public void Save(string path)

Parameters — destination is a writable stream, left open for the caller to dispose; path is a file to create or overwrite.

Exceptions — InvalidOperationException when nothing has been fitted yet. ArgumentNullException for a null stream or path. IOException from the stream or file system.

Example — saving and restoring, with the weights intact.

using Lodestar.Text.Vectorization;

var tv = new TfidfVectorizer();
tv.Fit(["the cat eats", "the dog eats"]);

using var buffer = new MemoryStream();
tv.Save(buffer);
buffer.Position = 0;

TfidfVectorizer restored = TfidfVectorizer.Load(buffer);
string first = restored.GetFeatureNames()[0];  // => cat

Remarks — what is written is both halves of the fit: the vocabulary and the document frequencies. That second half is the reason saving matters more here than for CountVectorizer — frequencies are a property of the training corpus, and a corpus that is gone cannot be measured again.

The stream overload leaves destination open, so a vectorizer can be one entry in a larger archive.

The write is not bounded the way a load is. A vocabulary past a default of ArtifactLoadOptions — a token over 1024 characters, more than a million features — saves, and loads only with that bound raised.

Applies to — net10.0, netstandard2.0.

See also — TfidfVectorizer.Load, TfidfVectorizer.SaveAsync.