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primaryobjects/climate_change.R

Created April 25, 2016 17:21
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Climate change dataset analysis, using linear regression.
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climate_change.R
data <- read.csv('climate_change.csv')
train <- subset(data, Year <= 2006)
test <- subset(data, Year > 2006)
fit <- lm(Temp ~ MEI + CO2 + CH4 + N2O + CFC.11 + CFC.12 + TSI + Aerosols, data=train)
fit2 <- lm(Temp ~ MEI + TSI + Aerosols + N2O, data=train)
# Auto-create model (note, step does not address the collinearity of the variables, so some features removed in fit2 are present in this model).
fit3 <- step(fit)
pred <- predict(fit3, newdata=test)
SSE <- sum((pred - test$Temp)^2)
SST <- sum((mean(train$Temp) - test$Temp)^2)
R2 <- 1 - SSE/SST
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