10 Questions
Which of the following is a reason why we need dimensionality reduction?
To reduce the number of features in a dataset
Which of the following is an approach for dimensionality reduction?
Feature selection
Which dimensionality reduction technique is based on finding the directions of maximum variance in a dataset?
Principal Component Analysis (PCA)
Which of the following datasets has the highest dimensionality?
A gene expression microarray with 100 samples and 27,000 genes
What are some costs associated with high dimensionality in datasets?
Data interpretation and visualization
Which of the following is NOT an approach for dimensionality reduction?
Data visualization
What is the dimensionality of the dataset mentioned in the text?
27,000
Which dimensionality reduction technique is based on finding the directions of maximum variance in a dataset?
Principal Component Analysis (PCA)
Which of the following datasets has the highest dimensionality?
Genomics with thousands of genes
What are some costs associated with high dimensionality in datasets?
Data interpretation and visualization
Test your knowledge on dimensionality reduction techniques in bioinformatics with this quiz. Explore the reasons for needing dimensionality reduction, different approaches, and specific methods like Principal Component Analysis (PCA) and Multi-dimensional scaling (MDS).
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