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Standardizing Your Data

In the lecture, we saw that you can learn a lot about a dataset by creating the matrix \(A^TA\) from it. In this exercise, you'll do that with athletic data for players entering the National Football League college draft. The dataset combine is loaded for you.

Questo esercizio fa parte del corso

Linear Algebra for Data Science in R

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Istruzioni dell'esercizio

  • Extract only the numerical elements of the data frame by taking only the 5th through 12th columns. Call this A (we cannot do math on the non-numerical components in columns 1 through 4).
  • Turn this data frame into a matrix by using the as.matrix() command.
  • Subtract the mean of each of the columns of the matrix.

Esercizio pratico interattivo

Prova a risolvere questo esercizio completando il codice di esempio.

# Extract columns 5-12 of combine
A <- combine[, ___:___]

# Make A into a matrix
A <- ___(A)

# Subtract the mean of each column
A[, ___] <- A[, 1] - mean(A[, 1])
A[, 2] <- A[, 2] - ___(A[, 2])
A[, ___] <- A[, 3] - mean(A[, 3])
A[, ___] <- A[, ___] - mean(A[, 4])
A[, 5] <- A[, 5] - mean(A[, 5])
A[, ___] <- A[, 6] - mean(A[, ___])
A[, 7] <- A[, ___] - mean(A[, 7])
A[, ___] <- A[, 8] - mean(A[, 8])
Modifica ed esegui il codice