IUM_06

metrics.py

@@ -9,10 +9,6 @@ def main():
     build_number = sys.argv[1]
 
     cm = confusion_matrix(y_test, y_pred)
-    print(
-        "Recall metric in the testing dataset: ",
-        cm[1, 1] / (cm[1, 0] + cm[1, 1]),
-    )
     accuracy = cm[1, 1] / (cm[1, 0] + cm[1, 1])
 
     with open(r"evaluation/metrics.txt", "a") as f:

plot.py

@@ -1,4 +1,3 @@
-import numpy as np
 import matplotlib.pyplot as plt
 
 
@@ -15,6 +14,7 @@ def main():
     plt.xlabel("Build Number")
     plt.ylabel("Accuracy")
     plt.title("Accuracy of the model over time")
+    plt.xticks(range(min(build_numbers), max(build_numbers) + 1))
     plt.show()
 
     plt.savefig("evaluation/accuracy.png")

predict.py

@@ -4,7 +4,6 @@ os.environ["TF_ENABLE_ONEDNN_OPTS"] = "0"
 
 from keras.models import load_model
 import pandas as pd
-from sklearn.metrics import confusion_matrix
 import numpy as np