Fixed intercept adjustment by prior probability in logistic regression.

src/main/java/hex/glm/GLM2.java

@@ -68,7 +68,7 @@ public void setTweediePower(double pwr){
   @API(help="disable line search in all cases.",filter=Default.class, importance = ParamImportance.EXPERT, hide = true)
   protected boolean disable_line_search = false; // -1 is magic value for default value which is mean(y) computed on the current dataset
 
-  private double _iceptAdjust; // adjustment due to the prior
+  private double _iceptAdjust = 0; // adjustment due to the prior
 
   @API(help = "validation folds", filter = Default.class, lmin=0, lmax=100, json=true, importance = ParamImportance.CRITICAL)
   protected int n_folds;
@@ -765,6 +765,8 @@ private String LogInfo(String msg){
     int intercept = (this.intercept ?1:0);
     double [] fullBeta = (_activeCols == null || newBeta == null)?newBeta:expandVec(newBeta,_activeCols);
     if(val != null) val.null_deviance = _nullDeviance;
+    if(this.intercept)
+      fullBeta[fullBeta.length-1] += _iceptAdjust;
     if(_noffsets > 0){
       fullBeta = Arrays.copyOf(fullBeta,fullBeta.length + _noffsets);
       if(this.intercept)
@@ -1164,14 +1166,7 @@ public void callback(final YMUTask ymut) {
         _ymu = ymut.ymu();
         _nobs = ymut.nobs();
         if(_glm.family == Family.binomial && prior != -1 && prior != _ymu && !Double.isNaN(prior)) {
-          double ratio = prior / _ymu;
-          double pi0 = 1, pi1 = 1;
-          if (ratio > 1) {
-            pi1 = 1.0 / ratio;
-          } else if (ratio < 1) {
-            pi0 = ratio;
-          }
-          _iceptAdjust = Math.log(pi0 / pi1);
+          _iceptAdjust = -Math.log(_ymu * (1-prior)/(prior * (1-_ymu)));
         } else prior = _ymu;
         H2OCountedCompleter cmp = (H2OCountedCompleter)getCompleter();
         cmp.addToPendingCount(1);