Across
- 1. the developed model is such that the user can only test the model but cannot know how it is working
- 3. learns through the induction process
- 10. error related to misestimating the mean
- 11. this problem can be solved by using constraints on model parameters
- 12. Transforms all the values of any attribute to zero mean and standard deviation one
- 13. fitting one example to a known class
Down
- 2. Correcting/removing inconsistencies, inaccuracy, irregularities etc in the data
- 3. the process that is used to classify nodes into two or more sub-nodes
- 4. Selecting right model
- 5. Computing linear correlation after ranking the variable values
- 6. used to control the learning process
- 7. In this case the training data does not include any desired output
- 8. A method that use the inbuilt structures in the data for a better organization of the data
- 9. Using many models to generate the estimate of the required categories Normally used any time you use a common noun