Model Fitting
When you click the Render button a document will be generated that includes both content and the output of embedded code. You can embed code like this:
The task is to predict the sf price onto the holdout dataset where the sf column is not present
Exploratory Analysis
head (training_data[2 : 11 ])
X1 X2 X3 runners favourite favourite_cloth_number jumps.flat
1 3.750000 29.000000 10.0 6 1.444444 6 Flat
2 4.500000 2.750000 13.0 9 2.750000 3 Flat
3 4.000000 1.727273 8.0 5 1.727273 4 Flat
4 1.727273 7.500000 5.0 6 1.727273 5 Flat
5 2.500000 6.500000 6.5 5 2.500000 2 Flat
6 2.500000 3.000000 4.0 5 2.500000 4 Jumps
places expert_opinion sf
1 2 NA 63.98
2 3 NA 11.27
3 2 NA 6.05
4 2 NA 7.07
5 2 NA 10.67
6 2 NA 5.29
X1 X2 X3 runners favourite favourite_cloth_number jumps.flat
1 3.750 4.500000 3.5 7 3.500000 3 Jumps
2 5.500 1.250000 13.0 3 1.250000 1 Jumps
3 4.500 10.000000 6.0 8 3.500000 5 Flat
4 9.000 4.333333 5.0 13 4.333333 12 Flat
5 2.375 2.750000 7.0 5 2.375000 4 Jumps
6 13.000 8.000000 26.0 16 3.750000 9 Jumps
places expert_opinion
1 2 NA
2 0 NA
3 2 NA
4 3 NA
5 2 NA
6 4 NA
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