naive_bayes.MultinomialNB
Usage
import { MultinomialNB } from 'machinelearn/naive_bayes';
const nb = new MultinomialNB();
const X = [[1, 20], [2, 21], [3, 22], [4, 22]];
const y = [1, 0, 1, 0];
nb.fit({ X, y });
nb.predict({ X: [[1, 20]] }); // returns [ 1 ]
Constructors
Methods
Constructors
constructor
⊕ MultinomialNB()
Defined in
Parameters:
| Param | Type | Default | Description |
|---|
Returns: MultinomialNB
Methods
λ fit
Fit date to build Gaussian Distribution summary
Defined in naive_bayes/multinomial.ts:48
Parameters:
| Param | Type | Default | Description |
|---|---|---|---|
| X | number[][] | null | training values |
| y | unknown | null | target values |
Returns:
void
λ fromJSON
Restore the model from states
Defined in naive_bayes/multinomial.ts:103
Parameters:
| Param | Type | Default | Description |
|---|---|---|---|
| classCategories | unknown | null | |
| multinomialDist | number[][] | null | |
| priorProbability | number[] | null |
Returns:
void
λ predict
Predict multiple rows
Defined in naive_bayes/multinomial.ts:62
Parameters:
| Param | Type | Default | Description |
|---|---|---|---|
| X | number[][] | null | values to predict in Matrix format |
Returns:
T[]
λ toJSON
Returns a model checkpoint
Defined in naive_bayes/multinomial.ts:75
Returns:
| Param | Type | Description |
|---|---|---|
| classCategories | T[] | List of class categories |