Forecasting, Data Science, Python, Data Visualization, Machine Learning.
Forecast: R library(forecast) library(ggplot2) # Load the data data <- AirPassengers # naive fit <- naive(data, h = 12) autoplot(fit) + ggtitle("Naive Forecast") + xlab("Year") + ylab("Passengers") B3. Naive Forecast: Fact Check In my 10 years of experience in data analytics, I never used this