APPLICATION OF SUPERVISED LEARNING
CLASSIFICATION IN MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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TRUE
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False
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Either A or B
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None of the above
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Detailed explanation-1: -Q7. [True or False] PCA can be used for projecting and visualizing data in lower dimensions. Explanation: Sometimes it is very useful to plot the data in lower dimensions. We can take the first 2 principal components and then use visualization of the data using a scatter plot.
Detailed explanation-2: -t-SNE is a nonlinear dimensionality reduction technique that is well suited for embedding high dimension data into lower dimensional data (2D or 3D) for data visualization.
Detailed explanation-3: -PCA is a simple yet popular method for handling high dimensional data and inspires many other methods.
Detailed explanation-4: -PCA generally tries to find the lower-dimensional surface to project the high-dimensional data. PCA works by considering the variance of each attribute because the high attribute shows the good split between the classes, and hence it reduces the dimensionality.