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| 1 | # Linear regression | |
| 2 | data = data.frame(X=c(25,28,35,32,31,36,29,38,34,32), Y = c(43,46,49,41,36,32,31,30,33,39)) | |
| 3 | model = lm(Y~X, data=data) | |
| 4 | test = data.frame(X=40) | |
| 5 | predict(model, test) | |
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| 7 | ||
| 8 | ### https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/datasets/data/boston_house_prices.csv | |
| 9 | data = read.csv("boston_house_prices.csv")
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| 10 | test = tail(data, n=2) | |
| 11 | train = head(data, n=-2) | |
| 12 | model = lm(MEDV ~ ., data=train) | |
| 13 | predict(model, train[50,]) | |
| 14 | test | |
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