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Exploring the traffic sign dataset

To better understand how the knn() function was able to classify the stop sign, it may help to examine the training dataset it used.

Each previously observed street sign was divided into a 4x4 grid, and the red, green, and blue level for each of the 16 center pixels is recorded as illustrated here.

Stop Sign Data Encoding

The result is a dataset that records the sign_type as well as 16 x 3 = 48 color properties of each sign.

Deze oefening maakt deel uit van de cursus

Supervised Learning in R: Classification

Cursus bekijken

Oefeninstructies

  • Use the str() function to examine the signs dataset.
  • Use table() to count the number of observations of each sign type by passing it the column containing the labels.
  • Run the provided aggregate() command to see whether the average red level might vary by sign type.

Praktische interactieve oefening

Probeer deze oefening eens door deze voorbeeldcode in te vullen.

# Examine the structure of the signs dataset


# Count the number of signs of each type
table(___)

# Check r10's average red level by sign type
aggregate(r10 ~ sign_type, data = signs, mean)
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