Verbose in Machine Learning-Python Tutorial-php.cn

Verbose in Machine Learning

Mary-Kate Olsen

Release： 2024-10-16 18:12:02

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Verbose

A flag in programming that controls the level of output generated during the execution of a program. It determines how much information is displayed to the user, ranging from no output (silent mode) to detailed logs that include progress updates, metrics, and additional diagnostic information.

Usage:

Verbose=0: No output is generated.
Verbose=1: Basic output is shown, typically including progress indicators.
Verbose=2: Detailed output is provided, including comprehensive metrics and additional logging.

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Verbose in Machine Learning

Table: Default Verbosity Levels in Machine Learning Frameworks

Framework	Default Verbosity	Description
Keras/TensorFlow	verbose=1	Basic output with a progress bar.
Scikit-Learn	Typically verbose=0	No verbosity set by default; varies by estimator. Most estimators default to 0.
XGBoost	verbosity=1	Displays warnings and progress information.
LightGBM	verbosity=1	Provides progress information during training.
PyTorch	No direct verbose flag	Logging can be controlled using different logging libraries.

Framework

Default Verbosity

Description

verbose=1

Basic output with a progress bar.

Scikit-Learn

Typically verbose=0

No verbosity set by default; varies by estimator. Most estimators default to 0.

XGBoost

verbosity=1

Displays warnings and progress information.

LightGBM

verbosity=1

Provides progress information during training.

PyTorch

No direct verbose flag

Logging can be controlled using different logging libraries.

When to use: Use verbose=0 for silent operations, batch processing, or production runs. Use verbose=1 for general training when you want basic updates. Use verbose=2 when you need to closely monitor every detail or are debugging the model.

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