Name: Trainable text classifier
Brand: Stellarr Studio
Availability: InStock

Contents and terms

A readable starting point for supervised text classification. This multinomial Naive Bayes implementation learns word frequencies per category, applies smoothing and exposes model scores. It abstains when no known term is present. Fictional messages exercise training, prediction and evaluation without customer data.

Included capabilities

Supervised category training
Smoothed log-probability calculations
Abstention for unknown vocabulary
Confusion matrix and per-class F1
Separate training and test examples

Licence and getting started

Original code under the MIT licence, copyright 2026 STELLARR STUDIO. Personal and commercial use permitted with the licence notice retained. French and English guides included. Trademarks and dependencies retain their own rights.

Read the README for requirements, start commands, tests and deployment limits. Hosting, compute, external APIs and bespoke support are not included.

Included files

.gitignore
classifier.py
examples/test.json
examples/train.json
kit.json
LICENSE
README.en.md
README.md
test_classifier.py
TEST_REPORT.md
THIRD_PARTY_NOTICES.md
verification.json

Getting started

01

Compatibility

The technologies on this page provide a starting point. Check exact versions, dependencies and requirements in the included guides before installation.

Python
Naive Bayes

02

Set up at your own pace

Download the archive from your account, extract it into a dedicated directory and follow README.md or README.en.md. Review commands and try the provided examples before using your own data.

03

An explicit scope

This page describes the delivered contents. Integration with your product or bespoke assistance is arranged separately with the studio. Usage rights are specified in the licence below.

Discuss a specific requirement

This resource’s licence

Read the complete terms before ordering. They define permitted uses and redistribution obligations.

Show the full textMIT

MIT License

Copyright (c) 2026 STELLARR STUDIO

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

Trainable text classifier

Contents and terms

Included capabilities

Licence and getting started

Included files

Getting started

Compatibility

Set up at your own pace

An explicit scope

This resource’s licence

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