diff --git a/compiler/characterizer/analytical_util.py b/compiler/characterizer/analytical_util.py
index 43435667..a4048a79 100644
--- a/compiler/characterizer/analytical_util.py
+++ b/compiler/characterizer/analytical_util.py
@@ -35,24 +35,31 @@ def get_data(file_name):
     with open(file_name, newline='') as csvfile:
         csv_reader = csv.reader(csvfile, delimiter=' ', quotechar='|')
         row_iter = 0
+        removed_items = 1
         for row in csv_reader:
             row_iter += 1
             if row_iter == 1:
                 feature_names = row[0].split(',')
-                input_list = [[] for _ in feature_names]
-                scaled_list = [[] for _ in feature_names]
+                input_list = [[] for _ in range(len(feature_names)-removed_items)]
+                scaled_list = [[] for _ in range(len(feature_names)-removed_items)]
+                # Save to remove area
+                area_ind = feature_names.index('area')
                 
                 try:
                     process_ind = feature_names.index('process')
                 except:
                     debug.error('Process not included as a feature.')
                 continue
+                
+                
 
             data = []
             split_str = row[0].split(',')
             for i in range(len(split_str)):
                 if i == process_ind:
                     data.append(process_transform[split_str[i]])
+                elif i == area_ind:
+                    continue
                 else:
                     data.append(float(split_str[i]))
 
diff --git a/compiler/characterizer/regression_model.py b/compiler/characterizer/regression_model.py
index d9c2359d..dd402dbd 100644
--- a/compiler/characterizer/regression_model.py
+++ b/compiler/characterizer/regression_model.py
@@ -57,10 +57,11 @@ class regression_model(simulation):
         model_inputs = [log_num_words, 
                         OPTS.word_size, 
                         OPTS.words_per_row, 
-                        self.sram.width * self.sram.height,
                         process_transform[self.process], 
                         self.vdd_voltage, 
                         self.temperature]  
+                        # Area removed for now
+                        # self.sram.width * self.sram.height,
 
         self.create_measurement_names()
         models = self.train_models()
@@ -92,10 +93,10 @@ class regression_model(simulation):
                     port_data[port]['disabled_read0_power'].append(sram_vals['read0_power'])
                         
                     debug.info(1, '{}, {}, {}, {}, {}'.format(slew, 
-                                                                                 load, 
-                                                                                 port, 
-                                                                                 sram_vals['delay_lh'], 
-                                                                                 sram_vals['slew_lh']))
+                                                              load, 
+                                                              port, 
+                                                              sram_vals['delay_lh'], 
+                                                              sram_vals['slew_lh']))
         # Estimate the period as double the delay with margin
         period_margin = 0.1
         sram_data = {"min_period": sram_vals['delay_lh'] * 2,