plot

evaluation.py

@@ -3,7 +3,7 @@ import re
 from sklearn import metrics
 import numpy as np
 import csv 
-
+import matplotlib.pyplot as plt
 f = open("result.txt", "r")
 
 list_result, list_predicted=[],[]
@@ -27,3 +27,21 @@ print("RMSE: ",metrics[2])
 with open('eval.csv', 'a', newline='') as f:
     writer = csv.writer(f)
     writer.writerow((metrics[0],metrics[1], metrics[2]))
+
+
+MAE,MSE,RMSE=[],[],[]
+with open('eval.csv', 'r') as r:
+    for row in r:
+        # row variable is a list that represents a row in csv
+        row=row.split(',')
+        MAE.append(float(row[0]))
+        MSE.append(float(row[1]))        
+        RMSE.append(float(row[2]))    
+
+
+plt.ylabel('F score')
+plt.plot(np.arange(0, len(MAE)), MAE)
+plt.plot(np.arange(0, len(MSE)), MSE) 
+plt.plot(np.arange(0, len(RMSE)), RMSE) 
+
+plt.savefig('metrics.png')