Across
- 6. Magnification factor in a linear transformation
- 10. One of the god fathers in AI
- 11. Variable inferred from other variable
- 12. Test to measure the ability to exhibit human behviour
- 14. Measure of linear relationship between two vectors
- 15. Functions that map data from one dimension to another dimesnion
- 16. A bad choice of loss function for classifiation
Down
- 1. Reduce variance & increase bias
- 2. Vector direction remains invariant to transformation
- 3. Measure of purity
- 4. In this all data points influence decision boundary
- 5. 'p' is the probablity of sucess & expected value of random variable is p
- 7. Focus on samples that are hard to classify
- 8. Projected data's covariance matrix is a diagonal matrix
- 9. Global & local minima are the same
- 13. Allows for feature selection