Question

17. ___ scale are differentiated by degree of difference with no absolute zero as part of the scale.

18. ___ is a situation in which a model explains random patterns in the data on which it is trained rather than just the relationships, resulting in training-set accuracy that far exceeds accuracy for the new data.

A) Model overfitting

B) Dimension Reduction

C) Model underfitting

D) Curse of dimensionality

22. Cautions in dealing with pattern discovery include:?

23. ___ occurs when the process that generates a data set changes of its own accord.

Answer 1

17. INTERVAL

Interval scale gives us the order of value and the ability to measure the difference between each one. It provides no absolute zero value.

18. Model overfitting

In this model, accuracy of the training is more than the accuracy of testing.

22. Poor data quality, oppurtunity, interventions, separability, obviousness, non-stationarity are the cautions which we are facing in dealing with pattern discovery.

23. Nonstationarity

Nonstationarity occurs when the process that generates a data set changes of its own accord. Nonstationarity means that the characteristics of the underlying processes we consider vary with time. There is no long run mean to which the series returns. The variance is time dependent.