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OCC Machine Learning Models Find Models that Have High Prediction Accuracy Ques

Question Description

Problem 2 (25 points): In your own words, describe:

  • the bias/variance tradeoff.
  • two methods of selecting features.
  • two approaches to compare/select models.
  • a method for selecting the best K for your KNN algorithm
  • a method for determining the best tree depth/ number of cases per parent node and number of cases per child node for your decision tree classifier.

Problem 3 (30 points): Sample of Data Science Interview questions

  • What is machine learning?
  • What is the difference between classification and regression?
  • What are feature vectors?
  • Explain the steps in building a decision tree.
  • Explain Random Forest? (what are the steps in creating a random forest classifier?)
  • What are two ways of reducing dimensionality.
  • Explain ROC curve and what is AUC?
  • What is bagging?
  • What is K-means?
  • What is overfitting?

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