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21:20 Here in confusion matrix, 25 should be true negative, instead of true positive. The output layout of sklearn.metrics.confusion_matrix is different from what we saw in regular confusion matrix.
A bit late but he explicitly said (although he stumbled with his words so I can understand your confusion) that whatever you fit (e.g. scaler) you must fit on the training (as that is the only data your model sees). You have to scale x_test however you use the scaler fit on training to do it. Now any future data will be scaled with a scaler that has been pre-trained.
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21:20
Here in confusion matrix, 25 should be true negative, instead of true positive.
The output layout of sklearn.metrics.confusion_matrix is different from what we saw in regular confusion matrix.
The number of predictions(n) depends on what??
If we have 5000 test data, what will be the number of predictions(n) for confusion matrix?
"Hi Shah,
n represents the total number of predictions made by the model. It is equal to the sum of TN+TP+FN+FP."
@@SimplilearnOfficial
Can YOU please make a video on
Confusion Matrix For Multiclass classification?
Well explained 👍 thanks
Thanks a ton!
On 17:34 you said that the test data should not be scaled.
On 18:42 you scale x_test.
I'm a bit confused.
A bit late but he explicitly said (although he stumbled with his words so I can understand your confusion) that whatever you fit (e.g. scaler) you must fit on the training (as that is the only data your model sees). You have to scale x_test however you use the scaler fit on training to do it. Now any future data will be scaled with a scaler that has been pre-trained.
Thank you!
You're welcome!
where is the dataset?
Hello, thanks for viewing our tutorial. You can find your requested dataset in the video description. Hope that helps.
41 people watched this in 7 minutes... WOOOW.
Oh yeah, first commenter!!!
Thanks for your love and support!
First
Nice!