machineLearning Test

A computer program is said to learn from __________E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E.

• Training

• Experience

• Database

• Algorithm

What takes input as an object described by a set of attributes?

• Tree

• Graph

• Decision graph

• Decision tree

Which of the following does not include different learning methods?

• Memorization

• Analogy

• Introduction

• Deduction

Which of the following is the model used for learning?

• Decision trees

• Neural networks

• Propositional and FOL rules

• All of the mentioned

In which of the following learning the teacher returns reward and punishment to learner?

• Active learning

• Reinforcement learning

• Supervised learning

• Unsupervised learning

Decision trees are appropriate for the problems where

• Attributes are both numeric and nominal

• Target function takes on a discrete number of values

• Data may have errors

• All of the mentioned

Full form of MDL.

• Minimum Domain Length

• Maximum Description Length

• Minimum Description Length

• None of these

The benefit of Naive Bayes:-

• Naive Bayes is one of the fast and easy ML algorithms to predict a class of data sets.

• It is the most popular choice for text classification problems

• It can be used for Binary as well as Multi-class Classifications

• All of the above

Examples of Naive Bayes Algorithm is/are

• Spam filtration

• Sentimental analysis

• Classifying articles

• All of the above

Which of the following is correct about the Naive Bayes?

• Assumes that all the features in a dataset are independent

• Assumes that all the features in a dataset are equally important

• Both

• All of the above