On This Page
This set of Machine Learning (ML) Multiple Choice Questions & Answers (MCQs) focuses on Machine Learning Set 14
Q1 | Features being classified is of each other in Nave Bayes Classifier
- independent
- dependent
- partial dependent
- none
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.
- true
- false
Q3 | In given image, P(H|E) is probability.
- posterior
- prior
Q4 | In given image, P(H)is probability.
- posterior
- prior
Q5 | Conditional probability is a measure of the probability of an event given that another
- true
- false
Q6 | Bayes theorem describes the probability of an event, based on prior knowledge of conditions that might be related to the event.
- true
- false
Q7 | Bernoulli Nave Bayes Classifier is distribution
- continuous
- discrete
- binary
Q8 | Multinomial Nave Bayes Classifier is distribution
- continuous
- discrete
- binary
Q9 | Gaussian Nave Bayes Classifier is distribution
- continuous
- discrete
- binary
Q10 | Binarize parameter in BernoulliNB scikit sets threshold for binarizing of sample features.
- true
- false
Q11 | Gaussian distribution when plotted, gives a bell shaped curve which is symmetric about the of the feature values.
- mean
- variance
- discrete
- random
Q12 | SVMs directly give us the posterior probabilities P(y = 1jx) and P(y = ??1jx)
- true
- false
Q13 | Any linear combination of the components of a multivariate Gaussian is a univariate Gaussian.
- true
- false
Q14 | Solving a non linear separation problem with a hard margin Kernelized SVM (Gaussian RBF Kernel) might lead to overfitting
- true
- false
Q15 | SVM is a algorithm
- classification
- clustering
- regression
- all
Q16 | SVM is a learning
- supervised
- unsupervised
- both
- none
Q17 | The linearSVMclassifier works by drawing a straight line between two classes
- true
- false
Q18 | Which of the following function provides unsupervised prediction ?
- cl_forecastb
- cl_nowcastc
- cl_precastd
- none of the mentioned
Q19 | Which of the following is characteristic of best machine learning method ?
- fast
- accuracy
- scalable
- all above
Q20 | What are the different Algorithm techniques in Machine Learning?
- supervised learning and semi-supervised learning
- unsupervised learning and transduction
- both a & b
- none of the mentioned
Q21 | What is the standard approach to supervised learning?
- split the set of example into the training set and the test
- group the set of example into the training set and the test
- a set of observed instances tries to induce a general rule
- learns programs from data
Q22 | Which of the following is not Machine Learning?
- artificial intelligence
- rule based inference
- both a & b
- none of the mentioned
Q23 | What is Model Selection in Machine Learning?
- the process of selecting models among different mathematical models, which are used to describe the same data set
- when a statistical model describes random error or noise instead of underlying relationship
- find interesting directions in data and find novel observations/ database cleaning
- all above
Q24 | Which are two techniques of Machine Learning ?
- genetic programming and inductive learning
- speech recognition and regression
- both a & b
- none of the mentioned
Q25 | Even if there are no actual supervisors learning is also based on feedback provided by the environment
- supervised
- reinforcement
- unsupervised
- none of the above