s444417/ium_444417
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

remove dolar from loss print
All checks were successful
s444417-training/pipeline/head This commit looks good
Details
s444417-evaluation/pipeline/head This commit looks good
Details

Browse Source
This commit is contained in:
s444417 2022-05-04 17:41:57 +02:00
parent b60eaddffc
commit 5a7c89711a
1 changed files with 10 additions and 10 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

20
src/evalScript.py
View File

@ -27,7 +27,7 @@ new_model = tf.keras.models.load_model(modelPath)
# Evaluate the restored model # Evaluate the restored model
loss = new_model.evaluate(house_price_test_features, house_price_test_expected, verbose=2) loss = new_model.evaluate(house_price_test_features, house_price_test_expected, verbose=2)
print("------\n") print("------\n")
print(f"loss result: ${loss}\n") print(f"loss result: {loss}\n")
print("------") print("------")
#print('Restored model, accuracy: {:5.2f}%'.format(100 * acc)) #print('Restored model, accuracy: {:5.2f}%'.format(100 * acc))
@ -47,14 +47,14 @@ try:
y = [] y = []
with open('trainResults.csv', 'r') as trainResults: with open('trainResults.csv', 'r') as trainResults:
plots = csv.reader(trainResults, delimiter = ',') plots = csv.reader(trainResults, delimiter = ',')
for row in plots: for row in plots:
x.append(row[0]) x.append(row[0])
y.append(row[1]) y.append(row[1])
plt.bar(x, y, color = 'g', label = "loss") plt.bar(x, y, color = 'g', label = "loss")
plt.xlabel('builds') plt.xlabel('builds')
plt.ylabel('losses') plt.ylabel('losses')
plt.title('loss for build') plt.title('loss for build')
plt.legend() plt.legend()
plt.show() plt.show()
except: except:
pass pass