00:01
For question one, so machine learning algorithm, they perform tasks and they also gain experience over time.
00:12
And it can also improve their performance based on the experience.
00:18
So that would be the all of the above.
00:24
So random force, it uses the bugging concept.
00:29
And they create an ensemble of decision trees for better predictions.
00:44
So that should be c random forest two.
00:53
Okay, so here handling missing or corrupted data can be done by dropping missing rows or columns.
01:02
And you can also assign a unique category to the missing.
01:10
Values or you can replace them with the mean median or mode.
01:16
So it should be d all of the above.
01:26
Or excuse me, that was this one was 3.
01:30
And this one is actually 4.
01:33
Okay, so this one is the training data because machine learning construct models from the sample data known as the training data.
01:51
5.
01:53
So you want to use, you want to do the evaluation, you want to evaluate the classification model...