Q.1
Machine Learning has various search/ optimization algorithms, which of the following is not evolutionary computation?
  • Perceptron
  • Genetic Algorithm (GA)
  • Neuro Evolution
  • Genetic Programming (GP)
Q.2
You are given reviews of movies marked as positive, negative, and neutral. Classifying reviews of a new movie is an example of
  • Supervised Learning
  • Unsupervised Learning
  • Reinforcement Learning
  • None of these
Q.3
ML is a field of AI consisting of learning algorithms that?
  • Improve their performance
  • At executing some task
  • Over time with experience
  • All of the above
Q.4
Targeted marketing, Recommended Systems, and Customer Segmentation are applications in
  • Unsupervised Learning: Clustering
  • Supervised Learning: Classification
  • Reinforcement Learning
  • Unsupervised Learning: Regression
Q.5
Several sets of data related to each other used to make decisions in machine learning algorithms
  • unsupervised learning
  • Classifiers
  • supervised learning
  • Dataset
Q.6
When would you reduce dimensions in your data?
  • When data comes from sensor
  • When you are using a Linux machine
  • When your data set is larger than 500GB
  • When you have larger set of features with similar characteristics
Q.7
How many types of machine learning?
  • 4
  • 3
  • 2
  • 1
Q.8
Which feature selection technique uses shrinkage estimators to remove redundant features from data?
  • Stepwise regression
  • Sequential feature selection
  • Neighborhood component selection
  • Regularization
Q.9
In a Decision Tree Leaf Node represents_____________
  • One of the Class Label
  • One of the complete observation
  • One of the attribute
  • None of the Mentioned
Q.10
High entropy means that the partitions in classification are
  • pure
  • not pure
  • useful
  • useless
Q.11
What kind of table compares classifications predicted by the model with the actual class labels?
  • Chaos table
  • Confusion Matrix
  • Prediction plot
  • Residual plot
Q.12
_________is the task of approximating a mapping function (f) from input variables (X) to a continuous output variable (Y).
  • Classification
  • Regression
  • Clustering
  • Decision Tree
Q.13
What would make a robot intelligent?
  • It responds to the environment.
  • It responds to the environment according to previous experiences.
  • It calculates mathematical problems faster than human minds.
  • It can jump 1.5 meters higher than humans.
Q.14
When performing regression or classification, which of the following is the correct way to preprocess the data?
  • Normalize the data -> PCA -> training
  • PCA -> normalize PCA output -> training
  • Normalize the data -> PCA -> normalize PCA output -> training
  • None of the above
Q.15
Machine Learning has various function representation, which of the following is not numerical functions?
  • Linear Regression
  • Support Vector Machines
  • Neural Network
  • Case-based
Q.16
Agglomerative clustering follows ________ .
  • model based clustering
  • top down approach.
  • bottom up approach
  • partitional clustering
Q.17
___________ is a type of supervised learning where a target feature, which is of categorical type.
  • Regression
  • Labelling
  • Classification
  • None
Q.18
All data is labeled and the algorithms learn to predict the output from the input data
  • Dataset
  • Classifiers
  • supervised learning
  • unsupervised learning
Q.19
Machine learning depends on?
  • how smart the person on the computer is
  • having a good machine
  • accessing an ever-growing database of increasingly complex information
  • All option correct
Q.20
How to choose the value of K in KNN?
  • Take the square root of the total data point available in the dataset.
  • Take the mean of the total data point available in the dataset.
  • Take the variance of the total data point available in the dataset.
  • Take the standard deviation of the total data point available in the dataset.
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