Machine Learning Set 14

Q1 | Features being classified is                    of each other in Nave Bayes Classifier

Q2 | Bayes Theorem is given by where 1. P(H) is the probability of hypothesis H being true.2. P(E) is the probability of the evidence(regardless of the hypothesis).3. P(E|H) is the probability of the evidence given that hypothesis is true.4. P(H|E) is the probability of the hypothesis given that the evidence is there.

Q3 | In given image, P(H|E) is                  probability.

Q4 | In given image, P(H)is                  probability.

Q5 | Conditional probability is a measure of the probability of an event given that another

Q6 | Bayes theorem describes the probability of an event, based on prior knowledge of conditions that might be related to the event.

Q7 | Bernoulli Nave Bayes Classifier is                    distribution

Q8 | Multinomial Nave Bayes Classifier is                    distribution

Q9 | Gaussian Nave Bayes Classifier is                    distribution

Q10 | Binarize parameter in BernoulliNB scikit sets threshold for binarizing of sample features.

Q11 | Gaussian distribution when plotted, gives a bell shaped curve which is symmetric about the               of the feature values.

Q12 | SVMs directly give us the posterior probabilities P(y = 1jx) and P(y = ??1jx)

Q13 | Any linear combination of the components of a multivariate Gaussian is a univariate Gaussian.

Q14 | Solving a non linear separation problem with a hard margin Kernelized SVM (Gaussian RBF Kernel) might lead to overfitting

Q15 | SVM is a algorithm

Q16 | SVM is a learning

Q17 | The linearSVMclassifier works by drawing a straight line between two classes

Q18 | Which of the following function provides unsupervised prediction ?

Q19 | Which of the following is characteristic of best machine learning method ?

Q20 | What are the different Algorithm techniques in Machine Learning?

Q21 | What is the standard approach to supervised learning?

Q22 | Which of the following is not Machine Learning?

Q23 | What is Model Selection in Machine Learning?

Q24 | Which are two techniques of Machine Learning ?

Q25 | Even if there are no actual supervisors               learning is also based on feedback provided by the environment