reorganize folder

[aggexp.git] / src / ml.predict_noNA.c

diff --git a/src/ml.predict_noNA.c b/src/ml.predict_noNA.c
deleted file mode 100644 (file)
index 03a5355..0000000
--- a/src/ml.predict_noNA.c
+++ /dev/null
@@ -1,64 +0,0 @@
-#include <math.h>
-#include <stdlib.h>
-
-void ml_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 initWeight = 1. / K;
-       for (int i=0; i<K; i++)
-               weight[i] = initWeight;
-       double* error = (double*)malloc(K*sizeof(double));
-       double* cumDeltaError = (double*)calloc(K, sizeof(double));
-       double* regret = (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;
-                       }
-               }
-
-               double hatError = 0.;
-               for (int i=0; i<K; i++)
-                       hatError += error[i] * weight[i];
-               for (int i=0; i<K; i++)
-               {
-                       double deltaError = hatError - error[i];
-                       cumDeltaError[i] += deltaError * deltaError;
-                       regret[i] += deltaError;
-                       double eta = 1. / (1. + cumDeltaError[i]);
-                       weight[i] = regret[i] > 0. ? eta * regret[i] : 0.;
-               }
-
-               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(cumDeltaError);
-       free(regret);
-}