random forests

Random forests are an ensemble machine learning method used to make predictions, such as classifying data or predicting values. Imagine a group of decision trees—each tree analyzes data and makes a prediction based on its rules. When combined, their predictions are aggregated, often by majority voting or averaging, to produce a final output. This approach leverages the strengths of multiple models to improve accuracy and reduce overfitting, making it a versatile and reliable tool for various data analysis tasks.