Visualize variance explained

Now you will create a scree plot showing the proportion of variance explained by each principal component, as well as the cumulative proportion of variance explained.

Recall from the video that these plots can help to determine the number of principal components to retain. One way to determine the number of principal components to retain is by looking for an elbow in the scree plot showing that as the number of principal components increases, the rate at which variance is explained decreases substantially. In the absence of a clear elbow, you can use the scree plot as a guide for setting a threshold.

Diese Übung ist Teil des Kurses

Unsupervised Learning in R

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Anleitung zur Übung

The proportion of variance explained is still available in the pve object you created in the last exercise.

Use plot() to plot the proportion of variance explained by each principal component.
Use plot() and cumsum() (cumulative sum) to plot the cumulative proportion of variance explained as a function of the number principal components.

Interaktive Übung

Versuche dich an dieser Übung, indem du diesen Beispielcode vervollständigst.

# Plot variance explained for each principal component
plot(___, xlab = "Principal Component",
     ylab = "Proportion of Variance Explained",
     ylim = c(0, 1), type = "b")

# Plot cumulative proportion of variance explained
plot(___, xlab = "Principal Component",
     ylab = "Cumulative Proportion of Variance Explained",
     ylim = c(0, 1), type = "b")

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