Summary

Summary Data Mining Linear regression (1+2) + solutions exercises

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Course
Data Mining

Institution
Universiteit Gent (UGent)

In this document, you can find a summary of the lab sessions on linear regression 1+2. In addition, you can also see the solutions to the exercises about linear regression 1+2.

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Uploaded on August 2, 2023
Number of pages 6
Written in 2022/2023
Type Summary

data mining
lab sessies
linear regression 1 2

Institution
Universiteit Gent (UGent)
Education
Handelsingenieur
Course
Data Mining

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Data Mining samenvatting alle lab sessies solutions exercises

$ 20.14 $ 8.59 6 items

1. Summary - Data mining introduction into r + solutions exercices (introduction)
2. Summary - Data mining linear regression (1+2) + solutions exercises
3. Summary - Data mining classification (1+2) + solutions exercises
4. Summary - Data mining resampling methods + solutions exercises
5. Summary - Data mining model selection and regularization + solutions exercises
6. Summary - Data mining unsupervised learning + solutions exercises
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Linear Regression 1
medv: median house value

rm: average number of rooms per house

age: average age of houses

lstat: percent of households with low socio-economic status

head(): the first n rows present in the input data frame

names(): access the variables names

lm(): fit a simple linear regression model

in general: lm(y ~ x, data), y = response and x = predictor, data = data set in which these two
variables are kept

in this example: error because R doesn’t find the variables, two solutions see below

lm.fit: gives basic information about the model its output

summary(lm.fit): for more detailed information (p-values, R 2 statistic, F-statistic…)

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