In time series forecasting, a moving average is a smoothing method in which the forecast for time t is the average value for the w periods ending with time t-1.
In regression models, an interaction term captures the joint effect of two variables that is not captured in the modeling of the two terms individually.
A naive forecast or prediction is one that is extremely simple and does not rely on a statistical model (or can be expressed as a very basic form of a model).
RMSE is root mean squared error. In predicting a numerical outcome with a statistical model, predicted values rarely match actual outcomes exactly.
A label is a category into which a record falls, usually in the context of predictive modeling. Label, class and category are different names for discrete values of a target (outcome) variable.