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Udemy CAP
| Question | Answer |
|---|---|
| Cross-Validation | helps determine the model's ability to generalize to unseen data |
| Descriptive models | best for identifying key trends and patterns in historical data. |
| Diagnostic models | analyze the effectiveness of new strategies by understanding past outcomes and performance |
| confusion matrix | is used to evaluate the performance of classification models by showing true and false positives/negatives |
| Defining the scope | helps avoid scope creep and keeps the project manageable |
| Implementing data access controls | ensures data integrity in a database |
| No autocorrelation | residuals are independent of each other |
| Pearson correlation | evaluates the relationship between two continuous variables |
| Breusch-Pagan test | is used to detect heteroscedasticity in regression models |
| data inventory in inquiring data | lists potential data sources |
| Overfitting | indicates that the model performs well on training data but poorly on new, unseen data |
| Linearity | implies that residuals should be independent of the independent variable |
| Why is it important to include both qualitative and quantitative aspects in a problem statement? | To ensure comprehensive understanding |
| What should be the focus when defining a business problem for analytics? | Business outcomes |
| Model bias | refers to the model's tendency to overfit or underfit, impacting its generalization ability |
| Cleaning the data | is a typical preparation step before analysis |
Created by:
ijadajackson