Definition of R-squared R-squared: R-squared is a statistic that measures how close the data points in a set are to a regression line (how well a model fits the data). It is a number between 0 and 1, with 1 indicating a perfect correlation and 0 indicating no correlation at all. It is calculated by…
Definition of Root Mean Squared Error Root Mean Squared Error: Root Mean Squared Error (RMSE) is a measure of the accuracy of predictions made by a model. It is calculated by taking the square root of the average of the squared differences between the actual values and the predicted values.
Definition of Resampling Resampling: Resampling is a technique used in data science to create new datasets from existing ones. It involves selecting a subset of the data to be used in the new dataset, and then randomly selecting samples from that subset. This process is repeated multiple times to create a new dataset that is…
Definition of Reinforcement Learning Reinforcement Learning: Reinforcement learning is a type of machine learning that allows machines to learn by trial and error. In reinforcement learning, the machine is given feedback after each trial, which allows it to learn which actions lead to positive outcomes. Reinforcement learning is often used to train robots or other…
Definition of Regression Regression: Regression is a technique used to model relationships between variables. It can be used to predict future values based on past values.
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.