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ML Introduction with scikit-learn

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Challenge: Creating a Pipeline

In this challenge, you need to put all the preprocessing steps we did together into one pipeline. The dataset is the initial penguins.csv file we started from.

The first step is to remove two useless rows. Then you will have to create a pipeline containing encoding, imputing, and scaling.

You need to encode only two columns, 'sex' and 'island'. Since you do not want to encode the entire X, you must use a ColumnTransformer. Afterward, apply the SimpleImputer and StandardScaler to the entire X.

Here is a reminder of the make_column_transformer() and make_pipeline() functions you will use.

Oppgave

Swipe to start coding

  1. Import the correct function for creating a pipeline.
  2. Make a ColumnTransformer with the OneHotEncoder applied only to columns 'sex' and 'island'.
  3. Make sure that all other columns remain untouched.
  4. Create a pipeline containing ct you just created, SimpleImputer that fills in missing values with the most frequent value and a StandardScaler as a last step.
  5. Transform the X using the pipe you created.

Løsning

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Alt var klart?

Hvordan kan vi forbedre det?

Takk for tilbakemeldingene dine!

Seksjon 3. Kapittel 4

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book
Challenge: Creating a Pipeline

In this challenge, you need to put all the preprocessing steps we did together into one pipeline. The dataset is the initial penguins.csv file we started from.

The first step is to remove two useless rows. Then you will have to create a pipeline containing encoding, imputing, and scaling.

You need to encode only two columns, 'sex' and 'island'. Since you do not want to encode the entire X, you must use a ColumnTransformer. Afterward, apply the SimpleImputer and StandardScaler to the entire X.

Here is a reminder of the make_column_transformer() and make_pipeline() functions you will use.

Oppgave

Swipe to start coding

  1. Import the correct function for creating a pipeline.
  2. Make a ColumnTransformer with the OneHotEncoder applied only to columns 'sex' and 'island'.
  3. Make sure that all other columns remain untouched.
  4. Create a pipeline containing ct you just created, SimpleImputer that fills in missing values with the most frequent value and a StandardScaler as a last step.
  5. Transform the X using the pipe you created.

Løsning

Switch to desktopBytt til skrivebordet for virkelighetspraksisFortsett der du er med et av alternativene nedenfor
Alt var klart?

Hvordan kan vi forbedre det?

Takk for tilbakemeldingene dine!

Seksjon 3. Kapittel 4
Switch to desktopBytt til skrivebordet for virkelighetspraksisFortsett der du er med et av alternativene nedenfor
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