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Classification Evaluations

  • Q. How would you evaluate a classification model?
  • Q. How would you evaluate a Classification model using ROC/AUC?
  • Q. What is Precision?
  • Q. What is Recall?
  • Q. What is F1 Score?
  • Q. What is Accuracy?
  • Q. What is Misclassification rate?
  • Q. What is False Positive Rate (FPR)?
  • Q. What is Specificity?
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  • Computer Vision (1)
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  • Machine Learning Basics (18)
  • Deep Learning (52)
    • DL Basics (16)
    • DL Architectures (17)
      • Feedforward Network / MLP (2)
      • Sequence models (6)
      • Transformers (9)
    • DL Training and Optimization (17)
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    • NLP Data Preparation (18)
  • Supervised Learning (115)
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      • Linear Regression (26)
      • Generalized Linear Models (9)
      • Regularization (6)
    • Classification (70)
      • Logistic Regression (10)
      • Support Vector Machine (9)
      • Ensemble Learning (24)
      • Other Classification Models (9)
      • Classification Evaluations (9)
  • Unsupervised Learning (55)
    • Clustering (37)
      • Distance Measures (9)
      • K-Means Clustering (9)
      • Hierarchical Clustering (3)
      • Gaussian Mixture Models (5)
      • Clustering Evaluations (6)
    • Dimensionality Reduction (9)
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    • Feature Engineering (30)
    • Sampling Techniques (5)
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Other Questions in Classification Evaluations
  • Explain the concept of Linear Regression
  • How are coefficients of linear regression estimated?
  • What are the assumptions of linear regression? 
  • How is variability measured in Linear Regression?
  • What are the evaluation criteria for a Linear Regression model? 
  • How can categorical predictors be incorporated in linear regression?
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