diff --git a/src/BaseEvaluator.java b/src/BaseEvaluator.java
index dc79bf2..c35659a 100644
--- a/src/BaseEvaluator.java
+++ b/src/BaseEvaluator.java
@@ -5,7 +5,7 @@ public class BaseEvaluator implements Evaluator{
     // when beta should use alpha's weights, have alpha commit to beta.csv and then call refreshWeights()
 
     protected WeightsParser wp;
-    String file;
+    protected String file;
     protected double[] weights;
 
     public BaseEvaluator(String file){
diff --git a/src/LearningEvaluator.java b/src/LearningEvaluator.java
index 8f31cac..b162954 100644
--- a/src/LearningEvaluator.java
+++ b/src/LearningEvaluator.java
@@ -5,6 +5,7 @@ public class LearningEvaluator extends BaseEvaluator{
 
     ArrayList<double[]> params;
     ArrayList<Double> values;
+    OLSMultipleLinearRegression reg; // performs linear regression (ordinary least squares)
     double alpha; // learning parameter, higher alpha means weights are closer to the regression output
                   // alpha of 1 is directly setting weights to be regression weights
                   // ideally we start at 1 and lower alpha to get a convergence
@@ -13,6 +14,7 @@ public LearningEvaluator(String file, double alpha){
         super(file);
         params = new ArrayList<double[]>();
         values = new ArrayList<Double>();
+        reg = new OLSMultipleLinearRegression();
         this.alpha = alpha;
 
     }
@@ -30,6 +32,26 @@ public void commitWeights(String path){
         this.wp.writeWeights(path, this.weights); // method to commit weights to beta. provide path to beta csv
     }
 
+    public void updateWeights(){
+        double[] vals = new double [values.size()];
+        for(int i = 0; i < values.size(); i++){
+            vals[i] = values.get(i);
+        }
+        values.clear();
+        double[][] pars = new double[params.size()][];
+        for(int i=0; i < params.size(); i++){
+            pars[i] = params.get(i);
+        }
+        params.clear();
+        reg.newSampleData(vals, pars);
+        reg.setNoIntercept(true);
+        double[] new_weights = reg.estimateRegressionParameters();
+        for(int i = 0; i < this.weights.length; i++){
+            this.weights[i] = this.weights[i] + alpha * (new_weights[i] - this.weights[i]);
+        }
+        commitWeights(this.file);
+
+    }