linear_model.Lasso
Usage
import { Iris } from 'machinelearn/datasets';
import { Lasso } from 'machinelearn/linear_model';
(async function() {
  const irisData = new Iris();
  const {
    data,         // returns the iris data (X)
    targets,      // list of target values (y)
  } = await irisData.load(); // loads the data internally
  const reg = new Lasso({ degree: 2, l1: 1 });
  reg.fit(data, target);
  reg.predict([[5.1,3.5,1.4,0.2]]);
})();
Constructors
Properties
Methods
Constructors
constructor
⊕ Lasso(__namedParameters: `object`)
Defined in linear_model/coordinate_descent.ts:103
Parameters:
| Param | Type | Default | Description | 
|---|---|---|---|
| options.degree | number | null | |
| options.epochs | number | 1000 | |
| options.l1 | number | ||
| options.learning_rate | number | 0.001 | 
Returns: Lasso
Properties
▸ epochs
Defined in linear_model/stochastic_gradient.ts:27
▸ learningRate
Defined in linear_model/stochastic_gradient.ts:26
▸ loss
Defined in linear_model/stochastic_gradient.ts:28
▸ regFactor
Defined in linear_model/stochastic_gradient.ts:29
Methods
λ fit
Fit model with coordinate descent.
Defined in linear_model/coordinate_descent.ts:141
Parameters:
| Param | Type | Default | Description | 
|---|---|---|---|
| X | number[][] | null | A matrix of samples | 
| y | number[] | null | A vector of targets | 
Returns:
void
λ fromJSON
Restore the model from a checkpoint
Defined in linear_model/stochastic_gradient.ts:151
Parameters:
| Param | Type | Default | Description | 
|---|---|---|---|
| options.epochs | number | 10000 | |
| options.learning_rate | number | 0.0001 | |
| options.random_state | number | null | |
| options.weights | number[] | [] | 
Returns:
void
λ predict
Predict using the linear model
Defined in linear_model/coordinate_descent.ts:151
Parameters:
| Param | Type | Default | Description | 
|---|---|---|---|
| X | number[][] | null | A matrix of test data | 
Returns:
number[]
λ toJSON
Save the model's checkpoint
Defined in linear_model/stochastic_gradient.ts:118
Returns:
| Param | Type | Description | 
|---|---|---|
| epochs | number | model training epochs | 
| learning_rate | number | model learning rate | 
| random_state | number | Number used to set a static random state | 
| weights | number[] | Model training weights |