Why is accuracy important in machine learning?

Why is accuracy important in machine learning?

Accuracy is crucial in machine learning as it measures how well a model predicts outcomes. High accuracy means reliable predictions.

What happens if a model has low accuracy?

Low accuracy can lead to incorrect predictions, which may result in poor decision-making and can be detrimental in critical applications.

How can we improve the accuracy of a machine learning model?

Improving accuracy can involve techniques like feature selection, hyperparameter tuning, and using more complex algorithms.

Are there any metrics besides accuracy to evaluate a model?

Yes, other metrics include precision, recall, F1 score, and AUC-ROC, which provide a more comprehensive evaluation of model performance.