What are some examples of parameters in machine learning?

What are some examples of parameters in machine learning?

In machine learning, parameters are the internal variables that the model learns from the training data. Examples include weights in neural networks, coefficients in linear regression, and the number of clusters in k-means clustering.

Can you explain how these parameters affect model performance?

Certainly! Parameters like weights in neural networks determine how input features are transformed into outputs. If they're not optimized, the model may underfit or overfit the data, leading to poor performance.

What techniques are used to optimize these parameters?

Common techniques include gradient descent, which adjusts parameters based on the error of predictions, and regularization methods that prevent overfitting by penalizing large parameter values.

Are there any tools that can help with parameter tuning?

Yes, tools like Grid Search, Random Search, and libraries such as Optuna and Hyperopt can help automate the process of parameter tuning to find the best model settings.