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Supervised learning and unsupervised clustering both require _____________________.

• input attribute
• hidden attribute
• output attribute
• categorical attribute

Which of the following techniques would perform better for reducing dimensions of a data set.

• removing columns which have high variance in data
• removing columns which have too many missing value
• removing columns with dissimilar data trends
• None of the above

Among the following option identify the one which is not a type of learning

• Semi unsupervised learning
• Supervised learning
• Reinforcement learning
• Unsupervised learning

The application of machine learning methods to a large database called.

• Data mining
• Internet of Things
• Big Data analysis
• Artificial Intelligence

Which of the following is/are example of supervised learning ________?

• Classification
• Regression
• Subgroup Discovery
• All of the above

You are given reviews of few Netflix series marked as positive, negative and neutral. Classifying reviews of a new Netflix series is an example of__________?

• Semi supervised Learning
• Unsupervised Learning
• Reinforcement Learning
• Supervised Learning

A machine learning problem involves four attributes plus a class. The attributes have 3, 2, 2, and 2 possible values each. The class has 3 possible values. How many maximum possible different examples are there?

• 25
• 12
• 72
• 48

Which of the following is/are true about Naïve Bayes? S1: Assumes that all the features in a dataset are independent. S2: Assumes that all the features in a dataset are equally important

• only S1 is true
• only S2 is true
• both S1 and S2 are true
• Neither S1 nor S2 is true

In PCA the number of input dimensions is equal to principal components.

• True
• False