a. When dimensionality increases, data becomes increasingly sparse

b. When dimensionality decreases, data becomes decreasingly sparse

c. When dimensionality increases, data becomes decreasingly sparse

d. The possible combinations of subspaces will grow exponentially

e. The possible combinations of subspaces will decreace exponentially

a. Linear regression is modeling data to fit a straight line

b. Linear regression often uses the least-square method to fit the line

c. Multiple regression allows a response variable Y to be modeled as a linear function of multidimensional feature vector

d. Long-linear model approximates discrete multidimensional probability distributions

e. Multiple regression is modeling data to fit for multiple straight line.

a. Simple random sampling

b. Smooth sampling

c. Sampling without replacement

d. Sampling with replacement

e. Stratified sampling