WorksheetsML Basics - 2
Total questions: 15
Worksheet time: 10mins
Machine Learning involves which of the following disciplines? (Choose 3 Answers)
Artificial Intelligence
Machine Learning
Data Statistics
Deep Learning
The task "Future stock prices or currency exchange rates" falls under which category?
Recognizing Anomalies
Prediction
Generating Patterns
Recognition Patterns
This picture shows an application of ...
Supervised Learning: Classification
Unsupervised Learning: Clustering
Unsupervised Learning: Prediction
Supervised Learning: Regression
Field of study that gives computers the ability to learn without being explicitly programmed.
Deep Learning
Machine Learning
Data Science
Estimating the price of a house is a problem solved through.....
Cluster
Class
Regression
According to Tom Mitchell, what is the requirement for the computer system to learn
Data set
Task
Performance measure
Knowledge
Select possible application of the machine learning ( Check all that apply)
Fraud detection
Recognising a happy face
Differentiate X-ray image
Recognise your lecturer's hand writing
What is the implication of "false positive" increase to the precision measure
increase precision
decrease precision
doesn't has any effect to precision
Suppose your email program watches which emails you do or do not mark as spam, and based on that learns how to better filter spam. What is the task T in this setting?
Classifying emails as spam or not spam
Watching you label emails as spam or not spam
The number of emails correctly classified as spam/not spam
None of the above
What type of Machine Learning Algorithm is suitable for predicting the continuous dependent variable?
Logistic Regression
Linear Regression
Decision Tree Classifier
KNN Classifier
The Number of coefficients required to estimate a simple linear regression?
( Hint: think of a simple linear regression equation)
1
2
0
3
KNN is ___________ algorithm
Eager Learner
Lazy Learner
Consider the above Confusion Matrix of a classifier and choose the correct statements
Accuracy is 84%
Misclassification Rate is 16%
Type-I Error is 6
Type-II Error is 10
If your algorithm gives very good accuracy for training set , but bad accuracy for test set, it is.......
Underfitting
Best fit
Overfitting
No Fit
Which ML algorithm is being used to perform classification in this image?
Naive Bayes
SVM
AVM
Decision Tree
