synced lda

1 files changed, 23 insertions, 1 deletions

diff --git a/parse_args.cc b/parse_args.cc
index 06964955..a3af35f6 100644
--- a/parse_args.cc
+++ b/parse_args.cc
@@ -53,6 +53,10 @@ po::variables_map parse_args(int argc, char *argv[], boost::program_options::opt
     ("initial_weight", po::value<float>(&global.initial_weight)->default_value(0.), "Set all weights to an initial value of 1.")
     ("initial_regressor,i", po::value< vector<string> >(), "Initial regressor(s)")
     ("initial_t", po::value<float>(&(par->t))->default_value(1.), "initial t value")
+    ("lda", po::value<size_t>(&global.lda), "Run lda with <int> topics")
+    ("lda_alpha", po::value<float>(&global.lda_alpha)->default_value(0.1), "Prior on sparsity of per-document topic weights")
+    ("lda_rho", po::value<float>(&global.lda_rho)->default_value(0.1), "Prior on sparsity of topic distributions")
+    ("lda_D", po::value<float>(&global.lda_D)->default_value(10000.), "Number of documents")
     ("min_prediction", po::value<double>(&global.min_label), "Smallest prediction to output")
     ("max_prediction", po::value<double>(&global.max_label), "Largest prediction to output")
     ("multisource", po::value<size_t>(), "multiple sources for daemon input")
@@ -68,6 +72,7 @@ po::variables_map parse_args(int argc, char *argv[], boost::program_options::opt
     ("quadratic,q", po::value< vector<string> > (),
      "Create and use quadratic features")
     ("quiet", "Don't output diagnostics")
+    ("random_weights", po::value<bool>(&global.random_weights), "make initial weights random")
     ("raw_predictions,r", po::value< string >(), 
      "File to output unnormalized predictions to")
     ("sendto", po::value< vector<string> >(), "send example to <hosts>")
@@ -103,6 +108,8 @@ po::variables_map parse_args(int argc, char *argv[], boost::program_options::opt
   global.print = print_result;
   global.min_label = 0.;
   global.max_label = 1.;
+  global.lda =0;
+  global.random_weights = false;
   
   global.adaptive = false;
   global.audit = false;
@@ -232,6 +239,21 @@ po::variables_map parse_args(int argc, char *argv[], boost::program_options::opt
 	}
     }
 
+  if (vm.count("lda"))
+    {
+      float temp = ceilf(logf((float)(global.lda+1)) / logf (2.f));
+      global.stride = powf(2,temp); 
+      global.random_weights = true;
+    }
+
+  if (vm.count("lda") && global.eta > 1.)
+    {
+      cerr << "your learning rate is too high, setting it to 1" << endl;
+      global.eta = min(global.eta,1.f);
+    }
+  if (!vm.count("lda"))
+    global.eta *= pow(par->t, vars.power_t);
+
   parse_regressor_args(vm, r, final_regressor_name, global.quiet);
 
   if (vm.count("active_c0"))
@@ -256,7 +278,7 @@ po::variables_map parse_args(int argc, char *argv[], boost::program_options::opt
   r.loss = getLossFunction(loss_function, loss_parameter);
   global.loss = r.loss;
 
-  global.eta *= pow(par->t, vars.power_t);
+//   global.eta *= pow(par->t, vars.power_t);
   
   if (global.eta_decay_rate != default_decay && global.numpasses == 1)
     cerr << "Warning: decay_learning_rate has no effect when there is only one pass" << endl;