Method testB

test/com/winvector/logistic/TestLog1.java:142–162

chosen to run to infinity > dat <- read.table('exB.txt',header=T,sep='\t') > model <- glm(y~x1+x2,family=binomial(link='logit'),data=dat) > predict(model,type='response') R soln: 23.56607 23.56607 -23.56607 reg(0.1) soln: x(0.1): 1 x 3 matrix -0.337079 2.215088 -0.642055

()

	 * 
	 */
	public void testB() {
		final double[][] dat = {
				///  x1  x2 y
				 {   1, 0,  1 },
				 {   1, 1,  1 },
				 {   0, 1,  0 }
		};
		final RExample ex = new RExample(dat);
		final Newton nwt = new Newton();
		final double reg = 0.1;
		final SigmoidLossMultinomial sigmoidLoss = new SigmoidLossMultinomial(ex.dim,2);
		final VectorFn sl = NormPenalty.addPenalty(new DataFn<ExampleRow>(new SigmoidLossMultinomial(ex.dim,2),ex),reg,null);
		final double[] x0 = new double[sl.dim()];
		final VEval opt = nwt.maximize(sl,x0,10);
		final double accuracy = HelperFns.accuracy(sigmoidLoss,ex,opt.x);
		assertTrue(accuracy>=1.0);
		for(int i=0;i<opt.x.length;++i) {
			assertTrue(Math.abs(opt.x[i])<5.0);
		}
		//System.out.println("x(" + reg + "): " + opt.x);
	}

}