WorksheetsMachine Learning Beginner Set - 1
Total questions: 15
Worksheet time: 10mins
What type of Machine Learning Algorithm is suitable for predicting the continuous dependent variable?
Logistic Regression
Linear Regression
Decision Tree Classifier
KNN Classifier
What type of Machine Learning Algorithm is suitable for predicting the dependent variable with two different values?
Logistic Regression
Linear Regression
Multiple Linear Regression
Polynomial Regression
None of These
Suitable evaluation metric for measuring the performance of a given regression model is -
ROC Curve
Precision
Recall
AUC Score
None of These
Appropriate chart for visualizing the linear relationship between two variables is ?
Scatter plot
Bar chart
Histograms
None of Mentioned
The Number of coefficients required to estimate a simple linear regression?
1
2
0
3
-1
The entropy of a given dataset is zero. This statement implies what?
further splitting is required
no further splitting is required
Need some other information to decide splitting
None of the Mentioned
If the given dataset contains 200 observations out of 100 belongs to class1 and other 100 belongs to class2. What will be the entropy of the given dataset?
0
1
-1
0.5
Consider a Confusion Matrix of a classifier where True Positive is 61, False Positive is 8, True Negative is 38 and False Negative is 5 then what is the correct statement
Accuracy is 81%
Misclassification Rate is 19%
Type-I Error is 8
Type-II Error is 13
None of them are True
Several sets of data related to each other used to make decisions in machine learning algorithms
Unsupervised Learning
Classifiers
Supervised Learning
Dataset
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
The process of making the system able to learn.
Classifying
Labelling
Testing
Training
Which model is good enough for fraud detection?
Precision = 60%, Recall = 60%
Precision = 60%, Recall = 90%
Precision = 90%, Recall = 60%
Precision = 90%, Recall = 90%
Select the true statements
Machine learning takes input data and static rules to predict the output value
Traditional programming analyses input data and comes up with rules and output data
Machine learning uses knowledge about input data and expected output to learn the rules for modelling data relationships
None of these are true statement
What device below is not an example of Machine Learning?
Google Assistant
Speech to Text
Google Search
None of the above
Which of the following is a good test dataset characteristic?
Large enough to yield meaningful results
Is representative of the dataset as a whole
Both of them are true
None of them are true
