Together, the first two principal components explain 87% of the variability. The Proportion of Variance Explained The first principal component in our example therefore explains 62% of the variability, and the second principal component explains 25%. How much of the variance in the data set is explained by each of the principal components? Ideally, you would choose the number of components to include in your model by adding the explained variance ratio of each component until you reach a total of around 0.8 or 80% to avoid overfitting. The explained variance ratio is the percentage of variance that is attributed by each of the selected components.
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