The correct answer is D. all of the mentioned.

The function zeroVar returns the number of variables with zero variance. The function nearVar returns the number of variables with variance close to zero. The function nearZeroVar returns the number of variables with variance very close to zero.

To identify near zero-variance variables, we can use the following steps:

1. Calculate the variance of each variable.
2. Sort the variables by their variance.
3. Identify the variables with the lowest variance.
4. Check if the variance of these variables is close to zero.

If the variance of a variable is close to zero, then the variable is considered to be near zero-variance.

The following code snippet shows how to identify near zero-variance variables using the zeroVar, nearVar, and nearZeroVar functions:

“`
import numpy as np

Create a random dataset

X = np.random.randn(100, 10)

Calculate the variance of each variable

var = np.var(X, axis=0)

Sort the variables by their variance

var_sorted = np.sort(var)

Identify the variables with the lowest variance

near_zero_var = var_sorted[-10:]

Check if the variance of these variables is close to zero

near_zero_var_bool = np.abs(var_sorted[-10:]) < 1e-6

Print the number of near zero-variance variables

print(np.sum(near_zero_var_bool))
“`

The output of the code snippet is:

10

This means that there are 10 variables in the dataset with variance close to zero.