Predict the values in Test.csv files using the developed ML model

Asked Feb 17 '22 at 13:00

Active Feb 17 '22 at 16:28

Viewed 49 times

array = [[]]

for i in range(len(test_data)):

  d = np.array(test_data.loc[i,test_data.columns],ndmin=2)

  value = loaded_model.predict(d)

  array.append(value)

My goal is to predict values in the test.csv files by using the devoloped model. I tried the above code which does not seem to be working. Getting the value error.

edited Feb 17 '22 at 16:28

James Z

12,209
10
24
44

asked Feb 17 '22 at 13:00

Praveen Manikanta

can you add what error is showing up? – Omar Feb 17 '22 at 13:15
[see if this helps you](https://stackoverflow.com/questions/52577999/feature-names-mismach-in-xgboost-despite-having-same-columns) – Omar Feb 17 '22 at 15:22
Got it. Thanks Following is the colab file link which I worked on: https://colab.research.google.com/drive/1f3xX4_zj6nrsAsqIriITLKe2_RphTtOP?usp=sharing – Praveen Manikanta Feb 17 '22 at 16:00
1

I am able to fix the error. Thank you so much @noober – Praveen Manikanta Feb 17 '22 at 16:40

Predict the values in Test.csv files using the developed ML model

0 Answers0