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# Logical Expressions Interview Questions and Answers

• September 06, 2022
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• ### Logistic regression method is _________________.

• a) Any type of output variable.
• b) Only for binary classification output.
• c) More than two outcomes.
• d) None of the above.

Answer - b) Only for binary classification output

• ### Mathematical understanding of the _________________and the natural logarithm function is used to understand what logistic regression is and how it works.

• a) Sigmoid function.
• b) Linear function.
• c) Tanh function.
• d) Relu function.

• ### The sigmoid function has values very close to either ____________across most of its domain.

• a) Infinity.
• b) Negative values.
• c) 0 or 1.
• d) Always 0.

Answer - c) 0 or 1

• ### The sigmoid function has values very close to either 0 or 1. This fact makes it suitable for application in ______________ methods.

• a) Classification.
• b) Continuous values prediction.
• c) Both (a) and (b).
• d) None of the above.

• ### In Python, _____________ represent the natural logarithm of x which is used while applying logistic regression.

• a) Only math.log(x).
• b) Only numpy.log(x).
• c) Math.log(x) and numpy.log(x) both.
• d) None of the above.

Answer - c) Math.log(x) and numpy.log(x) both

• ### Logistic regression is a linear classifier, so you’ll use a linear function (x) = b0 + b1x1 + ⋯ + brxr, also called the _____________.

• a) Logit.
• c) Log.
• d) None of the above.

• ### In Logistic regression is a linear classifier, so you’ll use a linear function (x) = b0 + b1x1 + ⋯ + brxr, where the variables b0, b1, …, br are called as _____________

• a) Estimators.
• b) Predicted weights.
• c) Coefficients.
• d) All of the above.

Answer - d) All of the above

• ### The logistic regression function (x) is the sigmoid function of f(x):p(x) =___________________.

• a) 1 / (1 + exp(-f(x)).
• b) (1 + exp(-f(x)).
• c) (1 - exp(-f(x)).
• d) None of the Above.

Answer - a) 1 / (1 + exp((-f(x))

• ### In Logistic regression ,the function p(x) is often interpreted as the predicted probability that the output for a given x is equal to 1. Therefore, 1-(x) is the probability that the output is __________.

• a) 1.
• b) Infinity.
• c) 0.
• d) None of the above.

• ### Logistic regression determines the best predicted weights b0, b1, …, br such that the function p(x) is as close as possible to all actual responses yi, i = 1, …, n, where n is the number of observations. The process of calculating the best weights using available observations is called ___________________.

• a) Data Preprocessing.
• b) Model Validating.
• c) Model training or fitting.
• D) All of the above.

Answer - c) Model training or fitting

• ### In Logistic regression to get the best weights, we usually maximize the log-likelihood function (LLF) for all observations i = 1, …, n. This method is called the ___________________ .

• a) Minimum likelihood estimation.
• b) Maximum likelihood estimation.
• c) True likelihood estimation.
• d) None of the above.

Answer - b) Maximum likelihood estimation

• ### The method maximum likelihood estimation is represented by the equation LLF = _________________ .

• a) Σi(yi log(p(xi)) + (1 - yi) log(1 -p(xi))).
• b) (yi log(p(xi)) + (1 - yi) log(1 -p(xi))).
• c) Σi(yi log(p(xi)) + (1 - yi) log(1 -p(xi))).
• d) None of the above.

Answer - a) Σi(yi log(p(xi)) + (1 - yi) log(1 -p(xi)))

• ### Binary classification has possible types of results, one of which is True negatives which means_________________ .

• a) Correctly predicted negatives (zeros).
• b) Correctly predicted positives (ones).
• c) Incorrectly predicted negatives (zeros).
• d) Incorrectly predicted positives (ones).

Answer - a) Correctly predicted negatives (zeros)

• ### Binary classification has possible types of results, one of which is True positives which means _________________ .

• a) Correctly predicted negatives (zeros).
• b) Correctly predicted positives (ones).
• c) Incorrectly predicted negatives (zeros).
• d) Incorrectly predicted positives (ones).

Answer - b) correctly predicted positives (ones)

• ### Binary classification has possible types of result, one of which is False negatives which means _________________ .

• a) Correctly predicted negatives (zeros).
• b) Correctly predicted positives (ones).
• c) Incorrectly predicted negatives (zeros).
• d) Incorrectly predicted positives (ones).

Answer - c) Incorrectly predicted negatives (zeros)

• ### Binary classification has possible types of result, one of which is False positives which means _________________ .

• a) Correctly predicted negatives (zeros).
• b) Correctly predicted positives (ones).
• c) Incorrectly predicted negatives (zeros).
• d) Incorrectly predicted positives (ones).

Answer - d) Incorrectly predicted positives (ones)

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