You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
I have a question about how to visualize the worst false positives and false negatives.
We have:
# Create DataFrame with validation sentences, validation labels and best performing model prediction labels + probabilitiesval_df=pd.DataFrame({"text": val_sentences,
"target": val_labels,
"pred": model_6_pretrained_preds,
"pred_prob": tf.squeeze(model_6_pretrained_pred_probs)})
val_df
# Find the wrong predictions and sort by prediction probabilitiesmost_wrong=val_df[val_df["target"] !=val_df["pred"]].sort_values(by="pred_prob", ascending=False)
most_wrong
most_wrong gives the false positives at the top of the list, but at the bottom we don't have the high probability false negatives but the lowest probability.
reacted with thumbs up emoji reacted with thumbs down emoji reacted with laugh emoji reacted with hooray emoji reacted with confused emoji reacted with heart emoji reacted with rocket emoji reacted with eyes emoji
-
Hello everyone!
I have a question about how to visualize the worst false positives and false negatives.
We have:
most_wrong gives the false positives at the top of the list, but at the bottom we don't have the high probability false negatives but the lowest probability.
Isn't it better to do it afterwards?:
The order of results is not at all the same for false negatives and seems more coherent to me, doesn't it?
Beta Was this translation helpful? Give feedback.
All reactions