[BUG]: missing multiplication in _modifiedHuberLoss implementation in ml/incr/binary-classification #13111

Description

I was going through the wikipedia pages as well as other library implementations of loss functions to implement standalone loss functions and their gradients under ml/base/loss/float64/*.
I noticed a possible bug in _modifiedHuberLoss function implemented under ml/incr/binary-classification

Current implementation:

setReadOnly( Model.prototype, '_modifiedHuberLoss', function modifiedHuber( x, y ) {
	var eta;
	var d;

	eta = this[ this._learningRateMethod ]();
	this._regularize( eta );

	d = y * this._dot( x.data, x.strides[ 0 ], x.offset );
	if ( d < -1.0 ) {
		this._add( x, 4.0*eta*y );
	} else {
		this._add( x, eta*( y-(d*y) ) );
	}
	return this;
});

Link

I believe in the else branch, it should be this._add( x, eta*2*( y-(d*y) ) ) instead of this._add( x, eta*( y-(d*y) ) ). That is, it seems like it is missing a multiplication with 2 here.

References:
Wikipedia
sklearn

cc: @Planeshifter

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Checklist

• Read and understood the Code of Conduct.
• Searched for existing issues and pull requests.