Imposta la griglia di iperparametri dell'albero

In questo esercizio imposterai manualmente la griglia di iperparametri che verrà usata per regolare l’albero di classificazione dt e trovare il classificatore ottimale nel prossimo esercizio.

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Machine Learning con modelli ad alberi in Python

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Istruzioni dell'esercizio

Definisci una griglia di iperparametri corrispondente a un dizionario Python chiamato params_dt con:
- la chiave 'max_depth' impostata a una lista di valori 2, 3 e 4
- la chiave 'min_samples_leaf' impostata a una lista di valori 0.12, 0.14, 0.16, 0.18

Esercizio pratico interattivo

Prova a risolvere questo esercizio completando il codice di esempio.

# Define params_dt
params_dt = ____

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Questo esercizio fa parte del corso

Machine Learning con modelli ad alberi in Python

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Esercizio in corso

Exercise 4: Cerca l'albero ottimale Exercise 5: Valuta l’albero ottimale Exercise 6: Ottimizzare gli iperparametri di una RF Exercise 7: Iperparametri delle Random Forest Exercise 8: Imposta la griglia di iperparametri di RF Exercise 9: Cerca la foresta ottimale Exercise 10: Valuta la foresta ottimale Exercise 11: Congratulazioni!