 Timestamp:
 02/05/14 09:47:42 (11 years ago)
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trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/FeatureSelection/FeatureSelection.cs
r9456 r10440 48 48 + "Where is the S is a N x d matrix containing the selected columns from N x k the matrix of all features X" + Environment.NewLine 49 49 + "For each feature the probability that it is selected is " + selectionProbability + "%" + Environment.NewLine 50 + "X(i,j) ~ N(0, 1) iid, w(i) ~ U(0, 10) iid, n ~ N(0, sigma(w*S) * SQRT(" + noiseRatio + "))" + Environment.NewLine50 + "X(i,j) ~ N(0, 1) iid, w(i) ~ U(0, 10) iid, n ~ N(0, sigma(w*S) * SQRT(" + noiseRatio / (1  noiseRatio) + "))" + Environment.NewLine 51 51 + "The noise level is " + noiseRatio + " * sigma, thus an optimal model has R² = " 52 52 + Math.Round(optimalRSquared, 2) + " (or equivalently: NMSE = " + noiseRatio + ")" + Environment.NewLine … … 131 131 } 132 132 var targetSigma = target.StandardDeviation(); 133 var noisePrng = new NormalDistributedRandom(random, 0, targetSigma * Math.Sqrt(noiseRatio ));133 var noisePrng = new NormalDistributedRandom(random, 0, targetSigma * Math.Sqrt(noiseRatio / (1.0  noiseRatio))); 134 134 135 135 data.Add(target.Select(t => t + noisePrng.NextDouble()).ToList());
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