External module "ml/incr/sgd-regression/docs/types/index.d"

Export assignment incrSGDRegression

• incrSGDRegression(options?: Options): Model

• Online learning for regression using stochastic gradient descent (SGD).

  Method

  The sub-gradient of the loss function is estimated for each datum and the regression model is updated incrementally, with a decreasing learning rate and regularization of the feature weights based on L2 regularization.

  References

  • Shalev-Shwartz, S., Singer, Y., Srebro, N., & Cotter, A. (2011). Pegasos: Primal estimated sub-gradient solver for SVM. Mathematical Programming, 127(1), 3–30. doi:10.1007/s10107-010-0420-4

  throws

  must provide valid options

  Parameters

  • Optional options: Options

    options object

  Returns Model

  regression model

  Example

  var incrSGDRegression = require( `@stdlib/streams/ml/incr/sgd-regression` );
  
  var accumulator = incrSGDRegression({
      'intercept': true
      'lambda': 1e-5
  });
  
  // Update model as observations come in:
  var y = 3.5;
  var x = [ 2.3, 1.0, 5.0 ];
  accumulator( x, y );
  
  // Predict new observation:
  var yHat = accumulator.predict( x );
  
  // Retrieve coefficients:
  var coefs = accumulator.coefs;