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WorksheetsMachine Learning
Total questions: 16
Worksheet time: 32mins
Which of the following is an example of a deterministic algorithm?
K-Means
PCA
Both of these
None of these
A feature F1 can take certain value: A, B, C, D, E, & F and represents grade of students from a college.
Which of the following statement is true in following case?
Feature F1 is an example of nominal variable.
Feature F1 is an example of ordinal variable.
It doesn’t belong to any of the above category.
Both (a) and (b)
What type of machine learning algorithm makes predictions when you have a set of input data and you know the possible responses?
Unsupervised
Reinforcement
Supervised
Deep Learning
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
Which feature selection technique uses shrinkage estimators to remove redundant features from data?
Stepwise regression
Sequential feature selection
Neighborhood component selection
Regularization
What is overfitting?
When a predictive model is accurate but takes too long to run
When the model learns specifics of the training data that can't be generalized to a larger data set
When you perform hyperparameter tuning and performance degrades
When you apply a powerful deep learning algorithm to a simple machine learning problem
What kind of table compares classifications predicted by the model with the actual class labels?
Chaos table
Confusion Matrix
Prediction plot
Residual plot
What kind of learning algorithm for "Future stock prices or currency exchange rates"?
Prediction
Recognizing Anomalies
Generating Patterns
Recognition Patterns
What kind of learning algorithm for "Facial identities or facial expressions"?
Recognizing Anomalies
Prediction
Generating Patterns
Recognition Patterns
Targeted marketing, Recommended Systems, and Customer Segmentation are applications in
Unsupervised Learning: Clustering
Supervised Learning: Classification
Reinforcement Learning
Unsupervised Learning: Regression
Machine Learning has various function representation, which of the following is not numerical functions?
Linear Regression
Support Vector Machines
Neural Network
Case-based
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
To find the minimum or the maximum of a function, we set the gradient to zero because:
The value of the gradient at extrema of a function is always zero
Depends on the type of problem
Both A and B
None of the above
How do you handle missing or corrupted data in a dataset?
Drop missing rows or columns
Replace missing values with mean/median/mode
Assign a unique category to missing values
All of the above
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
High entropy means that the partitions in classification are
pure
not pure
useful
useless
