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In optimisation problems Lagrangian is used to find out only the local minima of a function subject to certain constraints.

In optimisation problems Lagrangian is used to find out only the local minima of a function subject to certain constraints. Correct Answer False

In optimisation problems Lagrangian is used to find out both the local minima and maxima of a function subject to certain equality constraints. Lagrangian is the function in which the constraints have been introduced by multiplying them by positive coefficients called Lagrange multipliers.

Related Questions

In a group of 450 students, 22% of the total students take the Hindi subject, 34% of the total students take the Physics subject, and 26% of the total students take the Social Science subject. 8% of the total students have taken both Hindi and Physics subject only. Out of the total students in the Hindi subject, 1/3 have taken both Hindi and Social Science subject only. Out of the total students in the Physics subject, 1/3 have taken both Physics and Social Science subject only. Only 20 students take all the three subjects. Find the number of students who have not taken any subject.  
A Lagrange dual of a convex optimisation problem is another convex optimisation problem.
Imagine, you are solving a classification problems with highly imbalanced class. The majority class is observed 99% of times in the training data. Your model has 99% accuracy after taking the predictions on test data. Which of the following is true in such a case?
1. Accuracy metric is not a good idea for imbalanced class problems.
2.Accuracy metric is a good idea for imbalanced class problems.
3.Precision and recall metrics are good for imbalanced class problems.
4.Precision and recall metrics aren't good for imbalanced class problems.
There are 200 total students who like different subjects. Subjects available are Hindi, Mathematics, and English. Only Hindi is liked by 30 students, 50 students like all the subjects. 20 students like both Hindi and English subject, Math is liked by half of the student who like only Hindi subject. Only 35 students like both math and English and 10 students like only English subject. Based on the data find: How many students like math and Hindi both?
Akash scored 92 marks in subject A. He scored 68% marks in subject B and x marks in subject C. Maximum marks in each subject is 250. The overall percentage marks obtained by Akash in all the three subjects together were 44%. How many marks did he score in subject C?
Akash scored 73 marks in a subject A. He scored 56% in subject B and ‘x’ marks in subject C. Maximum marks in each subject were 150. The overall percentage marks obtained by Akash in the three subjects together were 54%. How many marks did he score in subject C?
Akash scored 71 marks in subject A. He scored 58% marks in subject B and x marks in subject C. Maximum marks in each subject were 150. The overall percentage marks obtained by Akash in all the three subjects together were 54%. How many marks did he score in subject C?
Engines are rated at specified conditions. Then which of the following statements are correct? 1. Power developed increases as local temperature increases. 2. Power developed increases as local temperature decreases 3. Power developed is not dependent on local temperature. 4. Power developed increases as local atmospheric pressure increases. 5. Power developed increases as local atmospheric pressure decreases.
There are 200 total students who like different subjects. Subjects available are Hindi, Mathematics, and English. Only Hindi is liked by 30 students, 50 students like all the subjects. 20 students like both Hindi and English subject, Math is liked by half of the student who likes only Hindi subject. Only 35 students like both math and English and 10 students like only English subject. Based on the data found: How many students like English Subjects?
Assuming Z and Y are the two control variables, the following are the constraints laid out for maximizing the profit: Maximize profit (P) = 8X – 5Y Subject to Constraint-1: 2X + Y ≤ 1000 Constraint-2: 3X + 4Y ≤ 2400 Constraint-3: X + Y ≤ 800 Constraint-4: X – Y ≤ 350 Constraint-5: X ≥ 0 Constraint-6: Y ≥ 0 Which of the above constraints is a redundant one and does not have any effect on the solution?