revert builtin

Author: Baunsgaard

scripts/builtin/l2svm.dml

@@ -88,8 +88,7 @@ m_l2svm = function(Matrix[Double] X, Matrix[Double] Y, Boolean intercept = FALSE
   w = matrix(0, rows=ncol(X), cols=1)
   Xw = matrix(0, rows=nrow(X), cols=1)
 
-  ## rewrite t(X) %*% Y
-  g_old = t(t(Y) %*% X)
+  g_old = t(X) %*% Y
   s = g_old
 
   iter = 0
@@ -122,9 +121,7 @@ m_l2svm = function(Matrix[Double] X, Matrix[Double] Y, Boolean intercept = FALSE
     sv = (out > 0)
     out = sv * out
     obj = 0.5 * sum(out * out) + reg/2 * sum(w * w)
-    ## rewrite t(X) %*% (out * Y) - reg * w
-    g_new = t(t(out*Y) %*% X) - reg * w
-    # g_new = t(X) %*% (out * Y) - reg * w
+    g_new = t(X) %*% (out * Y) - reg * w
 
     if(verbose) {
       colstr = ifelse(columnId!=-1, "-- MSVM class="+columnId+": ", "")

scripts/builtin/lmCG.dml

@@ -95,17 +95,15 @@ m_lmCG = function(Matrix[Double] X, Matrix[Double] y, Integer icpt = 0,
   lambda = scale_lambda * regularization
   beta_unscaled = matrix(0, rows = m_ext, cols = 1)
 
-  if((max_iteration == 0) | (max_iteration > m_ext)){
+  if(max_iteration == 0){
     max_iteration = m_ext
   }
   i = 0
 
   # BEGIN THE CONJUGATE GRADIENT ALGORITHM
   if(verbose) print("Running the CG algorithm...")
 
-  # Equivalent to - t(X) %*% y, we have a rewrite to detect it
-  # But CLA does not do it correctly... TODO to fix that rewrite.
-  r = - t(t(y) %*% X)
+  r = - t(X) %*% y
 
   if(intercept_status == 2){
     r = scale_X * r + shift_X %*% r [m_ext, ]
@@ -118,10 +116,8 @@ m_lmCG = function(Matrix[Double] X, Matrix[Double] y, Integer icpt = 0,
   if(verbose){
     print("||r|| initial value = " + sqrt(norm_r2_initial) +
       ", target value = " + sqrt(norm_r2_target))
-    print("Max Iteraton: " + max_iteration)
   }
 
-
   while(i < max_iteration & norm_r2 > norm_r2_target){
     if(intercept_status == 2){
       ssX_p = scale_X * p
@@ -132,15 +128,10 @@ m_lmCG = function(Matrix[Double] X, Matrix[Double] y, Integer icpt = 0,
 
     q = t(X) %*% (X %*% ssX_p)
 
-
-    
-
     if(intercept_status == 2) {
       q = scale_X * q + shift_X %*% q [m_ext, ]
     }
 
-    qi = q;
-
     q += lambda * p
     a = norm_r2 / sum(p * q)
     beta_unscaled += a * p
@@ -151,8 +142,7 @@ m_lmCG = function(Matrix[Double] X, Matrix[Double] y, Integer icpt = 0,
     i = i + 1
     if(verbose){
       print("Iteration " + i + ":  ||r|| / ||r init|| = "
-        + sqrt(norm_r2 / norm_r2_initial)
-        + "   :  " + sum(qi))
+        + sqrt(norm_r2 / norm_r2_initial))
     }
   }