DSE Knowledge 5

Question 1

What does the term 'data leakage' mean in a machine learning pipeline?

Accepted Answer

Information from the test set or future data inadvertently influencing model training

Answer

Data leakage occurs when information outside the legitimate training data is used to build the model, producing overly optimistic evaluation results.

Question 2

In the context of natural language processing, what does TF-IDF measure?

Accepted Answer

The importance of a word to a document relative to a corpus

Answer

TF-IDF weights a word by how frequently it appears in a document (TF) offset by how common it is across all documents (IDF), highlighting distinctive terms.

Question 3

What is a key difference between bagging and boosting ensemble methods?

Accepted Answer

Bagging trains models in parallel on bootstrap samples; boosting trains sequentially with error-focused reweighting

Answer

Bagging trains independent learners in parallel on random data subsets to reduce variance, while boosting trains sequentially to reduce both bias and variance.

Question 4

Which distance metric computes the sum of absolute differences between coordinates?

Accepted Answer

Manhattan distance

Answer

Manhattan (L1) distance sums the absolute differences along each dimension, geometrically resembling travel along city blocks.

Question 5

In time series analysis, what does 'stationarity' mean?

Accepted Answer

The statistical properties (mean, variance, autocorrelation) do not change over time

Answer

A stationary time series has constant statistical properties across time, which is a prerequisite for many forecasting models such as ARIMA.

DSE - Data Science Practice Test

DSE - Data Science Practice Test

DSE Knowledge 5