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In which scenario would you prefer using SVM over logistic regression?

Practice Questions

Q1
In which scenario would you prefer using SVM over logistic regression?
  1. When the dataset is small
  2. When the classes are linearly separable
  3. When the dataset has a high number of features
  4. When interpretability is crucial

Questions & Step-by-Step Solutions

In which scenario would you prefer using SVM over logistic regression?
  • Step 1: Understand what SVM (Support Vector Machine) is. It is a type of machine learning algorithm used for classification tasks.
  • Step 2: Understand what logistic regression is. It is another type of machine learning algorithm used for binary classification.
  • Step 3: Identify the characteristics of your dataset. Check if it has a lot of features (high-dimensional space).
  • Step 4: If your dataset has many features (like thousands of columns), consider using SVM because it works well in high-dimensional spaces.
  • Step 5: If your dataset has fewer features, logistic regression might be sufficient and easier to interpret.
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