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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.

Questo esercizio fa parte del corso

Machine Learning with PySpark

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Istruzioni dell'esercizio

  • 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.

Esercizio pratico interattivo

Prova a risolvere questo esercizio completando il codice di esempio.

# 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=____)
Modifica ed esegui il codice