StandardScaler
If the dataset is standardized, it will have a good optimization effect for many machine learning algorithms. To get standardized data you have to use the next formula:
Here we have the following values:
- x_scaled - standardized feature element,
- x - unnormalized feature element,
- mean - mean value,
- std - standard deviation value.
There is a function in the sklearn library that normalizes data according to the formula given above: MaxAbsScaler(). In order to work with this function, it must first be imported in such a way:
The main property of standardized data is that this data: mean = 0 and standard deviation = 1.
1from sklearn.preprocessing import StandarsScaler
This function works like the previous two, namely MinMaxScaler, MaxAbsScaler, and it works in a similar way. So, in this chapter there is no example of using StandartScaler function. You will use it on your own in the below task.
Let's try! If you have some difficulties, please, use hints.
Swipe to start coding
You have wine dataset, we have worked with it recently. Please, standardize this data. To check, if StandardScaler function works correct, please dispay the mean and standard deviation. Pay attention: mean will be equal to 0 and std to 1.
Oplossing
Bedankt voor je feedback!
single
Vraag AI
Vraag AI
Vraag wat u wilt of probeer een van de voorgestelde vragen om onze chat te starten.
Awesome!
Completion rate improved to 12.5StandardScaler
Veeg om het menu te tonen
If the dataset is standardized, it will have a good optimization effect for many machine learning algorithms. To get standardized data you have to use the next formula:
Here we have the following values:
- x_scaled - standardized feature element,
- x - unnormalized feature element,
- mean - mean value,
- std - standard deviation value.
There is a function in the sklearn library that normalizes data according to the formula given above: MaxAbsScaler(). In order to work with this function, it must first be imported in such a way:
The main property of standardized data is that this data: mean = 0 and standard deviation = 1.
1from sklearn.preprocessing import StandarsScaler
This function works like the previous two, namely MinMaxScaler, MaxAbsScaler, and it works in a similar way. So, in this chapter there is no example of using StandartScaler function. You will use it on your own in the below task.
Let's try! If you have some difficulties, please, use hints.
Swipe to start coding
You have wine dataset, we have worked with it recently. Please, standardize this data. To check, if StandardScaler function works correct, please dispay the mean and standard deviation. Pay attention: mean will be equal to 0 and std to 1.
Oplossing
Schakel over naar desktop voor praktijkervaringGa verder vanaf waar je bent met een van de onderstaande optiesBedankt voor je feedback!
Awesome!
Completion rate improved to 12.5single
