Data Balancing

Data balancing refers to the process of adjusting the distribution of different classes within a dataset so that they are more equally represented. In machine learning, this helps prevent models from becoming biased toward the more common classes, ensuring better accuracy across all categories. For example, if a dataset has many more images of cats than dogs, balancing techniques might add more dog images or reduce some cat images. This results in a more fair and effective model that can recognize both classes accurately.