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Summary Data Mining Linear regression (1+2) + solutions exercises R58,99   Add to cart
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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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Document information

  • August 2, 2023
  • 6
  • 2022/2023
  • Summary

Subjects

  • data mining
  • lab sessies
  • linear regression 1 2

Written for

  • Universiteit Gent (UGent)
  • Handelsingenieur
  • Data Mining
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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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