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Computer Science - Software Engineering

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user_pereira_de_andr Created by 7 mon ago

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Cards in this deck(22)
Under which category of machine learning is the K-Nearest Neighbor (KNN) algorithm classified?
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How does the K-Nearest Neighbor algorithm classify or predict new observations?
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What is the primary objective of the K-Nearest Neighbor algorithm?
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What are some advantages of using the K-Nearest Neighbor algorithm?
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What are some disadvantages of the K-Nearest Neighbor algorithm?
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What is the effect of choosing a smaller value for k in the K-Nearest Neighbor algorithm?
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What happens when you select a larger value for k in the K-Nearest Neighbor algorithm?
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What is a common starting point for selecting the parameter k in the K-Nearest Neighbor algorithm?
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How should you fine-tune the parameter k in the K-Nearest Neighbor algorithm?
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What is Multidimensional Scaling (MDS) used for in data analysis?
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How is Multidimensional Scaling (MDS) similar to Principal Component Analysis (PCA)?
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What is required to perform Multidimensional Scaling (MDS) on a dataset?
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What are the two types of Multidimensional Scaling (MDS) techniques?
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What is a key characteristic of Classical Multidimensional Scaling (MDS)?
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What is a feature of Non-metric MDS (Ordinal MDS)?
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What is the main difference between Principal Component Analysis (PCA) and Multidimensional Scaling (MDS)?
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When should you use Multidimensional Scaling (MDS) instead of Principal Component Analysis (PCA)?
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How does the curse of dimensionality affect model training in machine learning?
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What strategies can be used to mitigate the effects of the curse of dimensionality?
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What is a Simple Voting Ensemble in the context of model ensembles?
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How does a Proportion Voting Ensemble determine the final prediction?
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How do Average Ensembles work in model predictions?
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