Machine Learning: Machine learning is a subfield of artificial intelligence that enables computers to learn from data without being explicitly programmed. It focuses on the development of algorithms that can automatically learn to improve performance on a task as they are exposed to more data.
Definition of Mean Absolute Error Mean Absolute Error (MAE) is a measure of the accuracy of predictions made by a model. It is computed by taking the average of the absolute differences between the predicted values and the actual values for each observation. How is Mean Absolute Error used? Mean Absolute Error (MAE) is a…
Adaptive boosting, also known as AdaBoost, is a machine learning algorithm used to improve the accuracy of a classification model. It works by iteratively training a series of weak classifiers on a dataset, and then combining their predictions to produce a more accurate final prediction.
Definition of Random Forest Random forest: A random forest is a type of decision tree learner that builds a number of decision trees, rather than just one. The individual decision trees are then combined to create the random forest. This approach helps to avoid overfitting the data.
Definition of Mean Squared Error Mean Squared Error is a statistic used to measure the accuracy of predictions made by a machine learning model. It is calculated by taking the sum of the squared differences between the predicted values and the actual values for each data point, and dividing by the number of data points….