What is a random forest? * A random forest is a machine learning technique that’s used to solve regression and classification problems.  * It utilizes ensemble learning, which is a technique that combines many classifiers to provide solutions to complex problems. * A random forest algorithm consists of many decision trees. The ‘forest’ generated by the random forest algorithm is trained through bagging or bootstrap aggregating. * Bagging is an ensemble meta-algorithm that improves the accuracy of machine learning algorithms. * The (random forest) algorithm establishes the outcome based on the predictions of the decision trees.  * It predicts by taking the average or mean of the output from various trees. * Increasing the number of trees increases the precision of the outcome. *A random forest eradicates the limitations of a decision tree algorithm.  * It reduces the overfitting of datasets and increases precision.  * It generates predictions without requiring many co...