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diff --git a/pkg/src/ml.predict_noNA.c b/pkg/src/ml.predict_noNA.c
deleted file mode 100644
index 03a5355..0000000
--- a/pkg/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);
-}