Transform Labels Back To Original Encoding

I have a table like this: exterior_color interior_color ... isTheftRecovered price 0 Night Black Unknown ... 0 16995.0 1 Orca B

Solution 1:

By encoding as apply(LabelEncoder().fit_transform), you lose access to the encoder objects. Instead you can save them in an encoder dictionary keyed by column name:

from collections import defaultdict
encoder = defaultdict(LabelEncoder)

df[cols] = df[cols].apply(lambda x: encoder[x.name].fit_transform(x))

And then decode the final price via encoder['price']:

decoded = encoder['price'].inverse_transform(answer)[0]
print(f"Car's price has been predicted as ${decoded:.2f}")

# Car's price has been predicted as $16995.00