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POHow to include more outcomes on Infer.NET's BPM?
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  1. POHow to include more outcomes on Infer.NET's BPM?
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    copied!<p>How can I modify <a href="http://research.microsoft.com/infernet" rel="nofollow">Infer.NET</a>'s <a href="http://research.microsoft.com/en-us/um/cambridge/projects/infernet/docs/Bayes%20Point%20Machine%20tutorial.aspx" rel="nofollow">Tutorial 4: Bayes Point Machine</a> to include more outcomes?</p> <p>For example, how can I add willRent and get the separate probabilities for willBuy and willRent?</p> <pre><code> double[] incomes = { 63, 16, 28, 55, 22, 20 }; double[] ages = { 38, 23, 40, 27, 18, 40 }; bool[] willBuy = { true, false, true, true, false, false }; bool[] willRent = { false, false, true, false, true, false }; </code></pre> <p>Edit - Here's the example in copy/paste format:</p> <pre><code>static void Main() { double[] incomes = { 63, 16, 28, 55, 22, 20 }; double[] ages = { 38, 23, 40, 27, 18, 40 }; bool[] willBuy = { true, false, true, true, false, false }; // Create x vector, augmented by 1 Vector[] xdata = new Vector[incomes.Length]; for (int i = 0; i &lt; xdata.Length; i++) xdata[i] = Vector.FromArray(incomes[i], ages[i], 1); VariableArray&lt;Vector&gt; x = Variable.Observed(xdata); // Create target y VariableArray&lt;bool&gt; y = Variable.Observed(willBuy, x.Range); Variable&lt;Vector&gt; w = Variable.Random(new VectorGaussian(Vector.Zero(3), PositiveDefiniteMatrix.Identity(3))); Range j = y.Range; double noise = 0.1; y[j] = Variable.GaussianFromMeanAndVariance(Variable.InnerProduct(w, x[j]), noise) &gt; 0; InferenceEngine engine = new InferenceEngine(new ExpectationPropagation()); VectorGaussian wPosterior = engine.Infer&lt;VectorGaussian&gt;(w); Console.WriteLine("Dist over w=\n" + wPosterior); double[] incomesTest = { 58, 18, 22 }; double[] agesTest = { 36, 24, 37 }; VariableArray&lt;bool&gt; ytest = Variable.Array&lt;bool&gt;(new Range(agesTest.Length)); BayesPointMachine(incomesTest, agesTest, Variable.Random(wPosterior), ytest); Console.WriteLine("output=\n" + engine.Infer(ytest)); Console.ReadKey(); } static void BayesPointMachine(double[] incomes,double[] ages,Variable&lt;Vector&gt; w,VariableArray&lt;bool&gt; y) { // Create x vector, augmented by 1 Range j = y.Range; Vector[] xdata = new Vector[incomes.Length]; for (int i = 0; i &lt; xdata.Length; i++) xdata[i] = Vector.FromArray(incomes[i], ages[i], 1); VariableArray&lt;Vector&gt; x = Variable.Observed(xdata, j); // Bayes Point Machine double noise = 0.1; y[j] = Variable.GaussianFromMeanAndVariance(Variable.InnerProduct(w, x[j]), noise) &gt; 0; } </code></pre>
 

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