AI Math Knowledge
AI Knowledge
Sample Questions
-
Which of the following expressions is always equivalent to P(B A)P(A) - P(A U B)
-
P(A B) - P(A)P(B)
- P(A And B)
- A disease that occurs in 1% of the population has a test with a 3% false positive rate and a 6% false negative rate. If the test comes back positive for a random member of the population, what’s the probability they have the disease?
- 24%
- 94%
- 9%
- 97%
- When using a support vector machine on a training set with two classes, what’s the minimum possible number of support vectors?
- 0
- 1
- 2
- Depends on the dimension of the input data
- Which of the following assumptions does the Naive Bayes algorithm make?
- The input features are linearly independent
- The input features are conditionally independent
- The test data is linearly separable
- The test data is normally distributed
- Which of the following expressions defines the variance of a random variable X?
- E[X-E[X]^2
- E[X^2-E[X]]
- E[X-E[X]^2]
- E[X-E[X]]
- Which if the following is an application of singular value decomposition?
- Inverting a singular matrix
- Converting a matrix into Jordan form
- Finding a low-rank approximation of a matrix
- Solving an overdetermined system of linear equations
- Given the task of finding words which share a common prefix with a given word, which data structure would have the optimal expected asymptotic performance?
- binary tree
- sorted array
- hash set
- trie
- Which of the following approaches will help reduce overfitting?
- Switch to a model with more parameters
- Use a smaller training set
- Reduce the learning rate during gradient descent
- Add a regularization term to the cost function
- Which of the following approaches would give the best tradeoff between speed and accuracy when calculating the product of many probabilities?
- Use the log-sum-exp trick
- Use the Fourier transform trick
- Use a single-precision floating point type(float or float32)
- Use an arbitrary precision decimal type(BigDecimal in Java)
- Which of the following random variables cannot reasonably be considered “llD”?
- Repeatedly drawing,without replacement,from a deck of cards
- Repeatedly flipping a fair coin
- Repeatedly choosing a direction to move during an unbiased random walk
- Repeatedly flipping a biased coin that comes up heads with probability .7
- In a random forest classifier, which of the following choices involves randomness?
- Choosing which trees to discard during inference
- Choosing which loss function to use
- Choosing which branch to follow at a given node
- Choosing which subset of features to use for a given tree
- In general, how does the introduction of “regularization” affect a cost function?
- It doesn’t affect the cost function at all
- It ensures that the cost function is convex
- It penalizes large parameter values
- It adds a term to account for Gaussian noise