X-Git-Url: https://git.auder.net/doc/screen_pairings_scoring.png?a=blobdiff_plain;f=pkg%2Fsrc%2Few.predict_noNA.c;fp=pkg%2Fsrc%2Few.predict_noNA.c;h=33e3b8b2dd8d59d2bd2fa9a54b0b6a4761c3bdc2;hb=357b8be00388d07c04c10d4bf7f503fd947185d2;hp=0000000000000000000000000000000000000000;hpb=a961f8a15492bf4b18d24bc117358d1f412dd078;p=aggexp.git

diff --git a/pkg/src/ew.predict_noNA.c b/pkg/src/ew.predict_noNA.c
new file mode 100644
index 0000000..33e3b8b
--- /dev/null
+++ b/pkg/src/ew.predict_noNA.c
@@ -0,0 +1,69 @@
+#include <math.h>
+#include <stdlib.h>
+
+void ew_predict_noNA(double* X, double* Y, int* n_, int* K_, double* alpha_, int* grad_, double* weight)
+{
+	int K = *K_;
+	int n = *n_;
+	double alpha = *alpha_;
+	int grad = *grad_;
+
+	//at least two experts to combine: various inits
+	double invMaxError = 1. / 50; //TODO: magic number
+	double logK = log(K);
+	double initWeight = 1. / K;
+	for (int i=0; i<K; i++)
+		weight[i] = initWeight;
+	double* error = (double*)malloc(K*sizeof(double));
+	double* cumError = (double*)calloc(K, sizeof(double));
+
+	//start main loop
+	for (int t=0; t<n; t++ < n)
+	{
+		if (grad)
+		{
+			double hatY = 0.;
+			for (int i=0; i<K; i++)
+				hatY += X[t*K+i] * weight[i];
+			for (int i=0; i<K; i++)
+				error[i] = 2. * (hatY - Y[t]) * X[t*K+i];
+		}
+		else
+		{
+			for (int i=0; i<K; i++)
+			{
+				double delta = X[t*K+i] - Y[t];
+				error[i] = delta * delta;
+/*				if ((X[t*K+i] <= 30 && Y[t] > 30) || (X[t*K+i] > 30 && Y[t] <= 30))
+					error[i] = 1.0;
+				else
+					error[i] = 0.0;
+*/
+			}
+		}
+		for (int i=0; i<K; i++)
+			cumError[i] += error[i];
+
+		if (t < n-1 && !grad)
+		{
+			//weight update is useless
+			continue;
+		}
+
+		//double eta = invMaxError * sqrt(8*logK/(t+1)); //TODO: good formula ?
+		double eta = invMaxError * 1. / (t+1); //TODO: good formula ?
+		for (int i=0; i<K; i++)
+			weight[i] = exp(-eta * cumError[i]);
+		double sumWeight = 0.0;
+		for (int i=0; i<K; i++)
+			sumWeight += weight[i];
+		for (int i=0; i<K; i++)
+			weight[i] /= sumWeight;
+		//redistribute weights if alpha > 0 (all weights are 0 or more, sum > 0)
+		for (int i=0; i<K; i++)
+			weight[i] = (1. - alpha) * weight[i] + alpha/K;
+	}
+
+	free(error);
+	free(cumError);
+}