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I am not sure how to specify the "q" variable in the "Lq" loss function. I receive the following error message:

CatBoostError: /src/catboost/catboost/private/libs/options/catboost_options.cpp:82: Param q is mandatory for Lq loss

My code is as follows:

from catboost import CatBoostRegressor
from sklearn.datasets import make_regression
from sklearn.model_selection import train_test_split
import numpy as np

# Generate an artificial regression dataset
X, y = make_regression(n_samples=1000, n_features=10, random_state=42)

# Split the dataset into training and test sets
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

# Create a CatBoostRegressor object
model = CatBoostRegressor(loss_function='Lq')

# Fit the model 
model.fit(X_train, y_train)
desertnaut
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Felipe Polo
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1 Answers1

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The "Lq" loss function in CatBoost is the Lq loss, a generalization of the L1 and L2 losses. The "q" value is a parameter that controls the loss function's behavior. For example, when "q" is 1, the Lq loss function reduces to the L1 loss, and when "q" is 2, it becomes the L2 loss. The error message you're getting is indicating that you need to specify the "q" parameter for the Lq loss function.

You can specify the "q" parameter in the "loss_function" argument like this:

model = CatBoostRegressor(loss_function='Lq:q=2')  # here q=2

Please replace '2' with the desired "q" value that suits your particular use case. The silent=True argument is optional and simply suppresses the verbose output during model training.

tomasantunes
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