before the meeting

kernel_ridge_linear_model/best_R2_exploration_summary.csv

@@ -259,3 +259,7 @@ google_pixel_4a_5g,google_pixel_4a_5g_format,False,False,1000,0.01000000099,Fals
 google_pixel_4a_5g,google_pixel_4a_5g_format,False,False,1000,0.01000000099,False,----,0,1000000000.0,1000000000.0,1e-09,1000,0.1,100,False,0.6678084203477483,10,10,base_Y_F_N_on_socket,
 google_pixel_4a_5g,google_pixel_4a_5g_format,False,False,1000,0.01000000099,False,----,0,1000000000.0,1000000000.0,1e-09,1000,0.1,100,False,0.6678084203477483,10,10,base_Y_F_N_on_socket,
 google_pixel_4a_5g,google_pixel_4a_5g_format,False,False,1000,0.01000000099,False,----,0,1000000000.0,1000000000.0,1e-09,1000,0.1,100,False,0.6678084203477483,10,10,base_Y_F_N_on_socket,
+google_pixel_4a_5g,google_pixel_4a_5g_format,False,False,1000,0.01000000099,False,----,0,1000000000.0,1000000000.0,1e-09,1000,0.1,100,False,-296.89930270199477,10,10,base_Y_F_N_on_socket,
+google_pixel_4a_5g,google_pixel_4a_5g_format,False,False,1000,0.01000000099,False,----,0,1000000000.0,1000000000.0,1e-09,1000,0.1,100,False,-296.89930270199477,10,10,base_Y_F_N_on_socket,
+google_pixel_4a_5g,google_pixel_4a_5g_format,False,False,1000,0.01000000099,False,----,0,1000000000.0,1000000000.0,1e-09,1000,0.1,100,False,-296.89930270199477,10,10,base_Y_F_N_on_socket,
+google_pixel_4a_5g,google_pixel_4a_5g_format,False,False,1000,0.01000000099,False,----,0,1000000000.0,1000000000.0,1e-09,1000,0.1,100,False,-0.06746042254849738,10,10,base_Y_F_N_on_socket,

kernel_ridge_linear_model/kernel_ridge.py

@@ -142,7 +142,7 @@ else:
     y = data.get_y(phone_name)
     print ("*** Total energy efficiencies: ", y)
 
-
+"""
 print("--- Size of X before removing aberrants points from the dataset: ", len(X))
 X_len_before_removing_abberrant_points = len(X)
 utils.capture_X_y_in_file(np.array(X),  np.array(y), output_data_folder + "From_summaries_X_y_before_removing_aberrant_points.csv")
@@ -151,9 +151,9 @@ utils.capture_X_y_in_file(np.array(X),  np.array(y), output_data_folder + "From_
 print("--- Size of X after removing aberrants points from the dataset: ", len(X))
 print("--- Number of abberant points removed : ", X_len_before_removing_abberrant_points - len(X))
 print("*** Ratio energy by wokload : ", y)
+"""
 
-
-
+"""
 print("--- Size of X before removing duplicates: ", len(X))
 X_len_before_removing_duplicates = len(X)
 utils.capture_X_y_in_file(np.array(X),  np.array(y), output_data_folder + "From_summaries_X_y_before_removing_duplicate.csv")
@@ -162,7 +162,7 @@ utils.capture_X_y_in_file(np.array(X),  np.array(y), output_data_folder + "From_
 print("--- Size of X after removing duplicates: ", len(X))
 print("--- Number of duplicates points removed : ", X_len_before_removing_duplicates - len(X))
 print("*** Ratio energy by wokload : ", y)
-
+"""
 
 
 
@@ -270,6 +270,7 @@ if (generate_plots):
     if workstep == "looking_strange_cases":
         kernel_ridge_ax.bar(utils.get_X_user_friendly_from_X(X, X_dict),y, width=0.4)
         # Add title and axis names
+        print ("Size of X ---: ", len(X))
         kernel_ridge_ax.set_title('All energy/workload ratio')
         kernel_ridge_ax.set_xlabel('Configuration')
         kernel_ridge_ax.set_ylabel(r'Energy consumed/Workload ($\times 10E-11$)')

kernel_ridge_linear_model/model_output_data/From_summaries_X_y_after_removing_aberrant_points.csv

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kernel_ridge_linear_model/model_output_data/From_summaries_X_y_after_removing_duplicate.csv

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kernel_ridge_linear_model/model_output_data/From_summaries_X_y_before_removing_aberrant_points.csv

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kernel_ridge_linear_model/model_output_data/From_summaries_X_y_before_removing_duplicate.csv

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