ML5

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

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