ok

rabit-learn/README.md

@@ -8,6 +8,8 @@ It also contain links to the Machine Learning packages that uses rabit.
 Toolkits
 ====
 * [KMeans Clustering](kmeans)
+* [Linear and Logistic Regression](liner)
+  
 * [XGBoost: eXtreme Gradient Boosting](https://github.com/tqchen/xgboost/tree/master/multi-node)
   - xgboost is a very fast boosted tree(also known as GBDT) library, that can run more than
     10 times faster than existing packages

rabit-learn/linear/Makefile

@@ -11,5 +11,3 @@ CFLAGS+=-fopenmp
 linear.o: linear.cc ../../src/*.h linear.h ../solver/*.h
 # dependenies here
 linear.rabit: linear.o lib
-
-

rabit-learn/linear/README.md

@@ -2,3 +2,28 @@ Linear and Logistic Regression
 ====
 * input format: LibSVM
 * Example: [run-linear.sh](run-linear.sh)
+
+Parameters
+===
+All the parameters can be set by param=value
+
+#### Important Parameters
+* reg_L1 [default = 0]
+  - l1 regularization co-efficient
+* reg_L2 [default = 1]
+  - l2 regularization co-efficient
+* lbfgs_stop_tol [default = 1e-5]
+  - relative tolerance level of loss reduction with respect to initial loss
+* max_lbfgs_iter [default = 500]
+  - maximum number of lbfgs iterations
+
+### Optimization Related parameters
+* min_lbfgs_iter [default = 5]
+  - minimum number of lbfgs iterations
+* max_linesearch_iter [default = 100] 
+  - maximum number of iterations in linesearch
+* linesearch_c1 [default = 1e-4] 
+  - c1 co-efficient in backoff linesearch
+* linesarch_backoff [default = 0.5]
+  - backoff ratio in linesearch
+ 

rabit-learn/solver/lbfgs.h

@@ -57,12 +57,12 @@ class LBFGSSolver {
   LBFGSSolver(void) {
     // set default values
     reg_L1 = 0.0f;
-    max_linesearch_iter = 1000;
+    max_linesearch_iter = 100;
     linesearch_backoff = 0.5f;
     linesearch_c1 = 1e-4;
     min_lbfgs_iter = 5;
-    max_lbfgs_iter = 1000;
-    lbfgs_stop_tol = 3e-6f;
+    max_lbfgs_iter = 500;
+    lbfgs_stop_tol = 1e-5f;
     silent = 0;
   }
   virtual ~LBFGSSolver(void) {}
@@ -90,6 +90,15 @@ class LBFGSSolver {
     if (!strcmp("max_linesearch_iter", name)) {
       max_linesearch_iter = atoi(val);
     }
+    if (!strcmp("max_lbfgs_iter", name)) {
+      max_lbfgs_iter = atoi(val);
+    }
+    if (!strcmp("min_lbfgs_iter", name)) {
+      min_lbfgs_iter = atoi(val);
+    }
+    if (!strcmp("linesearch_c1", name)) {
+      linesearch_c1 = static_cast<float>(atof(val));
+    }
   }
   /*!
    * \brief set objective function to optimize