---
title: "ComplementNB in JavaScript with @kanaries/ml"
description: "Classify imbalanced non-negative count features with the ComplementNB JavaScript and TypeScript implementation in @kanaries/ml."
canonical_url: "https://ml.kanaries.net/docs/apis/bayes/complementNB"
markdown_url: "https://ml.kanaries.net/docs/apis/bayes/complementNB.md"
---
# ComplementNB in JavaScript

## Algorithm overview

ComplementNB is a naive Bayes variant designed for non-negative count features and often useful on imbalanced text-like classification problems. It estimates feature weights from the complement of each class.

## JavaScript implementation

`@kanaries/ml` exposes `Bayes.ComplementNB` so JavaScript and TypeScript applications can run this lightweight classifier in browser or Node.js environments.

## Quick start example

```ts
import { Bayes } from '@kanaries/ml';

const X = [[3, 0, 1], [2, 0, 1], [0, 2, 2], [0, 3, 1]];
const y = [0, 0, 1, 1];

const clf = new Bayes.ComplementNB({ alpha: 1.0, norm: false });
clf.fit(X, y);
const pred = clf.predict([[2, 0, 1], [0, 2, 1]]);
console.log(pred);
```

## Detailed API reference

```ts
new Bayes.ComplementNB(props?: {
  alpha?: number;
  forceAlpha?: boolean;
  fitPrior?: boolean;
  classPrior?: number[] | null;
  norm?: boolean;
})
```

Methods:

- `fit(X: number[][], y: number[]): void`
- `predict(X: number[][]): number[]`

Feature values must be non-negative.