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Measure the greenhouse baseline

BOTIE

Calculate the mean of the training temperatures without using the held-out days.
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0 passed · 0 failed · 2 not run

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Context for this challenge

Calculate the mean of the training temperatures without using the held-out days.

Botie needs a reference score before adding a more complicated temperature model. Fit one constant on training data and evaluate it on the held-out temperatures.

Inspect the component calculation
Mean(
  Numbers: Training temperatures
)
Examples and results
Training temperatures
  1. 010
  2. 114
  3. 218
Required result
14
Training temperatures
  1. 02
  2. 14
  3. 26
Required result
4
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Assumptions and test precision

This baseline uses no input features. Its score is a comparison, not a guarantee of acceptable temperature prediction. Numerical tests allow a difference of 0.001. Lists and structures must also have the right shape.

Your last tested pieces can start the full construction. An existing draft there keeps its own pieces.

A skewed training set and an exact held-out hit

This check uses the pieces from “Score the training-mean baseline on held-out days”.

BOTIE

Fit the constant prediction from the training temperatures, then predict its mean squared error on the held-out days. One held-out reading equals the training mean.
Training temperatures
  1. 00
  2. 10
  3. 212
Held-out temperatures
  1. 04
  2. 110
  3. 21

Use a number, text, or an array matching the requested result. For a matrix, put each row in brackets. Saving your prediction runs your current construction on these inputs and checks the earlier examples too.

Build a construction in the workspace above first. This case will test those pieces.

Why must competing models use the same test days, and what could a model with extra features legitimately improve beyond this baseline?

Set a simple, properly evaluated reference before deciding that model complexity is useful.

This baseline uses no input features. Its score is a comparison, not a guarantee of acceptable temperature prediction.

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