Hi all, I am close to figuring this out but not quite. I’m trying to grade the accuracy of predictions from a predicted dataframe, and so I gather the predictions into a DataFrame like so:
predictions = learn.get_preds(DatasetType.Test).numpy() preds = pd.DataFrame(predictions)
The result of this is a location of the proper label from learn.data.classes, so I saved that array as arr. Let
truth be the test dataframe:
i = 0 predictions = learn.get_preds(DatasetType.Test).numpy() preds = pd.DataFrame(predictions) arr = learn.data.classes for x in range(len(preds)): if(arr[int(preds.iloc[x])] == truth.iloc[x]): i+=1 print(i/len(truth))
This should be working for generating an overall accuracy, but it reports back 44%. When I verify what the accuracy should be via learn.predict() over the entire dataframe I report an accuracy of 94.3%. Did I do something wrong with the above?
Thank you very much for your help!