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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