Across
- 1. An ensemble machine-learning algorithm that blends various estimator predictions in a meta-learning algorithm
- 3. A phenomenon occurs when a model has not learned the patterns in the training data well and is unable to generalize well on the new data
- 6. The process of applying an algorithmic model built from a historical dataset to a new dataset in order to uncover practical insights that will help solve a business problem
- 9. A subset of individuals or observations selected from a larger population
- 12. The differences between the observed values of the dependent variable and the values predicted by the regression model
- 13. An observation or data point that significantly differs from the other observations in a dataset
- 14. A non-parametric measure of statistical dependence between two variables, calculated over the ranked values
Down
- 2. The process of configuring the implementation-specific parameters that act as control knobs to guide learning
- 4. A type of n-gram model which consists of sequences of three consecutive characters/words in a text
- 5. An optimized distributed gradient boosting library designed for efficient and scalable training of machine learning models
- 6. The process of transforming variables or features to a standard range or distribution
- 7. The value separating the higher half from the lower half of data
- 8. The changes in the model when using different portions of the training data set
- 10. The process of analyzing and transforming raw data into a structured and usable format
- 11. A rectangular array of numbers, symbols, or expressions arranged in rows and columns