There are currently no frequently asked questions associated with this exercise – that’s where you come in! You can contribute to this section by offering your own questions, answers, or clarifications on this exercise. Ask or answer a question by clicking reply () below.

If you’ve had an “aha” moment about the concepts, formatting, syntax, or anything else with this exercise, consider sharing those insights! Teaching others and answering their questions is one of the best ways to learn and stay sharp.

Join the Discussion. Help a fellow learner on their journey.

Ask or answer a question about this exercise by clicking reply () below!

Agree with a comment or answer? Like () to up-vote the contribution!

How is defined the quantity of splitted sets. In the lesson’ example it is 3. Though, in the function split(cars, car_labels, 3) - 3 is the index of the column and not the quantity of sets.

Hi there!
I have troubles understanding understanding the split function given in this exercise (although it isn’t explained anywhere).

def split(dataset, labels, column):
data_subsets = []
label_subsets = []
counts = list(set([data[column] for data in dataset]))
counts.sort()
for k in counts:
new_data_subset = []
new_label_subset = []
for i in range(len(dataset)):
if dataset[i][column] == k:
new_data_subset.append(dataset[i])
new_label_subset.append(labels[i])
data_subsets.append(new_data_subset)
label_subsets.append(new_label_subset)
return data_subsets, label_subsets

I think the reason for using set() is to eliminate duplicates. The list comprehension creates a list of the values at the index column of all data in the dataset, and the set() returns a set object where duplicates are eliminated. We make it a list object again with list().

I think “Method 3” of the following page is easy to understand as an example:

agreed, this just comes out of nowhere, how are we supposed to be able to understand this?

I mean I understand what this function does, create subsets of the data based on specific properties, be it number of doors, how many people the car can hold, size of the trunk, etc.

I just don’t get why has this function be implemented? There is no background provided and just appeared from nowhere.

There are six (we have 6 features) times we make new data_set, but here the point - we make only one step looking for the best features to find best gain after those step.
Hope I help you!