Merge branch 'caret' into pc_new_1

4 files changed, 12 insertions, 17 deletions

diff --git a/README.md b/README.md
index e854ac3..e979ff6 100644
--- a/README.md
+++ b/README.md
@@ -35,19 +35,19 @@ REST operations
                                                         [feature_generation_uri],
                                                         [prediction_algorithm],
                                                         [feature_dataset_uri],
-                                                        [propositionalized=false],
                                                         [pc_type=null],
-                                                        [nr_hits=false (class.), true (regr.)],
-                                                        [min_sim=0.3 (nominal), 0.6 (numeric features)]
+                                                        [nr_hits=false (class. using wt. maj. vote), true (else)],
+                                                        [min_sim=0.3 (nominal), 0.4 (numeric features)]
+                                                        [min_train_performance=0.1]
 
 Synopsis
 --------
 
-- prediction\_algorithm: One of "weighted\_majority\_vote" (default for classification),  "local\_svm\_classification", "local\_svm\_regression (default for regression)", "local\_mlr\_prop". "weighted\_majority\_vote"  is not applicable for regression. "local\_mlr\_prop" is not applicable for classification.
-- propositionalized: One of "true", "false". Not appplicable when prediction\_algorithm="weighted\_majority\_vote".
+- prediction\_algorithm: One of "weighted\_majority\_vote" (default for classification),  "local\_svm\_classification", "local\_svm\_regression" (default for regression). "weighted\_majority\_vote"  is not applicable for regression.
 - pc_type: Mandatory for feature dataset, one of [geometrical, topological, electronic, constitutional, hybrid, cpsa].
-- nr_hits: Whether for instantiated models (local\_svm\_kernel = "propositionalized" for prediction_algorithm="local\_svm\_classification" or "local\_svm\_regression", or for prediction_algorithm="local\_mlr\_prop") nominal features should be instantiated with their occurrence counts in the instances. For non-instantiated models (local\_svm\_kernel = "weighted\_tanimoto" for prediction_algorithm="local\_svm\_classification" or "local\_svm\_regression", or for prediction_algorithm="weighted\_majority\_vote") the neighbor-to-neighbor and neighbor-to-query similarity also integrates these counts, when the parameter is set. One of "true", "false". 
-- min_sim: The minimum similarity threshold for neighbors. Numeric value in [0,1]. 
+- nr_hits: Whether nominal features should be instantiated with their occurrence counts in the instances. One of "true", "false". 
+- min_sim: The minimum similarity threshold for neighbors. Numeric value in [0,1].
+- min_train_performance. The minimum training performance for "local\_svm\_classification" (Accuracy) and "local\_svm\_regression" (R-squared). Numeric value in [0,1].
 
 See http://www.maunz.de/wordpress/opentox/2011/lazar-models-and-how-to-trigger-them for a graphical overview.
 
diff --git a/last-utils b/last-utils
-Subproject 8c02f7e71450cac6d8c5d7d34ecb620046b4ea4
+Subproject cf0238477127e54509b6ab8b5c38f50dd6ffce0
diff --git a/lazar.rb b/lazar.rb
index 65752ec..81929c6 100644
--- a/lazar.rb
+++ b/lazar.rb
@@ -93,20 +93,19 @@ post '/lazar/?' do
     min_sim = params[:min_sim].to_f if params[:min_sim]
     min_sim = 0.3 unless params[:min_sim]
 
+    # Algorithm
+    lazar.prediction_algorithm = "Neighbors.#{params[:prediction_algorithm]}" if params[:prediction_algorithm]
+
     # Nr Hits
     nr_hits = false
-    if params[:nr_hits] == "true"
+    if params[:nr_hits] == "true" || lazar.prediction_algorithm.include?("local_svm")
       lazar.feature_calculation_algorithm = "Substructure.match_hits"
       nr_hits = true
     end
     params[:nr_hits] = "true" if lazar.feature_calculation_algorithm == "Substructure.match_hits" #not sure if this line in needed 
 
-    # Algorithm
-    lazar.prediction_algorithm = "Neighbors.#{params[:prediction_algorithm]}" if params[:prediction_algorithm]
-
     # Propositionalization
-    propositionalized = false
-    propositionalized = true if ( params[:propositionalized] != "false" && ( lazar.prediction_algorithm == "local_mlr_prop" || lazar.prediction_algorithm.include?("local_svm") )  )
+    propositionalized = (lazar.prediction_algorithm=="Neighbors.weighted_majority_vote" ? false : true)
    
     # PC type
     pc_type = params[:pc_type] unless params[:pc_type].nil?
@@ -115,10 +114,6 @@ post '/lazar/?' do
     min_train_performance = params[:min_train_performance].to_f if params[:min_train_performance]
     min_train_performance = 0.1 unless params[:min_train_performance]
 
-    # Conf_stdev --- To be removed??
-    lazar.conf_stdev = ( (params[:conf_stdev] == "true") ? true : false ) 
- 
-
 
 
 
diff --git a/libfminer b/libfminer
-Subproject 17932e809c35c93374ed3d5fd19a313325c35b4
+Subproject f9e560dc0a7a5d5af439814ab5fa9ce027a025b