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Flight duration model: Pipeline stages

You're going to create the stages for the flights duration model pipeline. You will use these in the next exercise to build a pipeline and to create a regression model.

The StringIndexer, OneHotEncoder, VectorAssembler and LinearRegression classes are already imported.

Den här övningen är en del av kursen

Machine Learning with PySpark

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Övningsinstruktioner

  • Create an indexer to convert the 'org' column into an indexed column called 'org_idx'.
  • Create a one-hot encoder to convert the 'org_idx' and 'dow' columns into dummy variable columns called 'org_dummy' and 'dow_dummy'.
  • Create an assembler which will combine the 'km' column with the two dummy variable columns. The output column should be called 'features'.
  • Create a linear regression object to predict flight duration.

You might find it useful to revisit the slides from the lessons in the Slides panel next to the IPython Shell.

Interaktiv övning med praktiskt arbete

Testa den här övningen genom att slutföra den här exempelkoden.

# Convert categorical strings to index values
indexer = ____(____)

# One-hot encode index values
onehot = ____(
    inputCols=____,
    outputCols=____
)

# Assemble predictors into a single column
assembler = ____(inputCols=____, outputCol=____)

# A linear regression object
regression = ____(labelCol=____)
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