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WorksheetsWeekly Quiz 1
Total questions: 10
Worksheet time: 6mins
Adding a new feature to the model always results in equal or better performance on the training set?
True
False
Which of these isn’t a classification type?
Binary Classification
Multi-class multilabel
Single class multilabel
Multi-class Single Label
Which of these is not a supervised learning algorithm?
Representation Learning
Classification
Regression
Which of these metrics are used to evaluate classification algorithm?
F1 Score
AUC
Predicted vs True Chart
Precision
_____ is a learning model that is used to identify a relationship between large amounts of information from a data set.
Classification
Association
Unsupervised Learning
Multiclass Classification
A computer program is said to learn from experience E with respect to some task T and some performance measure P if its performance on T, as measured by P, improves with experience E. Suppose we feed a learning algorithm a lot of historical weather data, and have it learn to predict weather. In this setting, what is E?
Historical weather data.
The process of the algorithm examining a large amount of historical weather data.
Learning Rate
Performance measure
What should be the ideal split percentage for data in machine learning?
training data (70%), test data (10%), validation data (20%)
training data (50%), test data (20%), validation data (30%)
test data (70%), training data (10%), validation data (20%)
test data (20%), training data (70%), validation data (10%)
Which of the following options is/are true for K-fold cross-validation?
Increase in K will result in higher time required to cross validate the result.
Higher values of K will result in higher confidence on the cross-validation result as compared to lower value of K.
If K=N, then it is called Leave one out cross validation, where N is the number of observations.
Which of the following option is true for overall execution time for 5-fold cross validation with 10 different values of “max_depth”?
Less than 100 seconds
100 – 300 seconds
Can’t estimate
More than or equal to 600 seconds
None of the above
Imagine you are working on a project which is a binary classification problem. You trained a model on training dataset and get the below confusion matrix on validation dataset.
Based on the above confusion matrix, choose which option(s) below will give you correct predictions?
Accuracy is ~0.91
Misclassification rate is ~ 0.91
False positive rate is ~0.95
True positive rate is ~0.95
