model.rb in libmf-0.2.5

- old
+ new

@@ -12,29 +12,35 @@
           eval_set = create_problem(eval_set)
           FFI.mf_train_with_validation(train_set, eval_set, param)
         else
           FFI.mf_train(train_set, param)
         end
+      raise Error, "fit failed" if @model.null?
 
       nil
     end
 
     def predict(row, column)
       FFI.mf_predict(model, row, column)
     end
 
     def cv(data, folds: 5)
       problem = create_problem(data)
-      FFI.mf_cross_validation(problem, folds, param)
+      # TODO update fork to differentiate between bad parameters and zero error
+      res = FFI.mf_cross_validation(problem, folds, param)
+      raise Error, "cv failed" if res == 0
+      res
     end
 
     def save_model(path)
-      FFI.mf_save_model(model, path)
+      status = FFI.mf_save_model(model, path)
+      raise Error, "Cannot save model" if status != 0
     end
 
     def load_model(path)
       @model = FFI.mf_load_model(path)
+      raise Error, "Cannot open model" if @model.null?
     end
 
     def rows
       model[:m]
     end
@@ -78,10 +84,26 @@
     end
 
     def param
       param = FFI.mf_get_default_param
       options = @options.dup
+
+      if options[:loss].is_a?(Symbol)
+        loss_map = {
+          real_l2: 0,
+          real_l1: 1,
+          real_kl: 2,
+          binary_log: 5,
+          binary_l2: 6,
+          binary_l1: 7,
+          one_class_row: 10,
+          one_class_col: 11,
+          one_class_l2: 12
+        }
+        options[:loss] = loss_map[options[:loss]] || (raise ArgumentError, "Unknown loss")
+      end
+
       # silence insufficient blocks warning with default params
       options[:bins] ||= 25 unless options[:nr_bins]
       options[:copy_data] = false unless options.key?(:copy_data)
       options_map = {
         :loss => :fun,
@@ -103,9 +125,13 @@
 
     def create_problem(data)
       if data.is_a?(String)
         # need to expand path so it's absolute
         return FFI.mf_read_problem(File.expand_path(data))
+      end
+
+      if data.is_a?(Matrix)
+        data = data.data
       end
 
       raise Error, "No data" if data.empty?
 
       # TODO do in C for better performance