NEW
Font size
WorksheetsMachine Learning
Total questions: 17
Worksheet time: 9mins
FIND-S algorithm ignores ______.
Negative
Positive
With positive or negative
Neither positive nor negative
Which of the following is a limitation of the FIND-S algorithm?
It can handle noisy data effectively
It can only find the most specific hypothesis
It is computationally expensive
It requires a large amount of labeled data
________ is not a supervised ML algorithm.
K-means clustering
SVM for classification
problems
Decision Tree
Naive Bayes
Which type of data is used in supervised learning?
Unlabeled data
Labeled data
Both
Neither
What is the primary goal of machine learning?
To manually program computers
To enable systems to learn from data
To simulate human intelligence
To enhance computer hardware speed
Which of the following is NOT a common machine learning task?
Classification
Regression
Sorting
Clustering
A model performs well on training data but poorly on test data. This is called____
Underfitting
Overfitting
Insufficient data
Testing data errors
What is the primary goal of regression in machine learning?
To classify data
To predict continuous values
To cluster data
To reduce dimensionality
What is the primary goal of unsupervised learning?
To label data
To classify data
To find patterns in unlabeled data
To split data
What distinguishes reinforcement learning from other learning paradigms?
The use of labeled data
Learning from unlabeled data
Learning through rewards and penalties
None of the above
What is the assumptions of Naïve Bayesian classifier?
It assumes that features of a data are completely dependent on each other
It assumes that each input variable is dependent and the model is not generative
It assumes that each input attributes are independent of each other and the model is generative
It assumes that the data dimensions are dependent and the model is generative
Which of the following is an example of a linear regression problem?
Predicting the probability of a user clicking on an ad
Predicting house prices
Classifying emails
Detecting fraudulent transactions
Which of the following is an example of a binary classification problem?
Predicting house prices
Classifying emails as spam or not
Clustering customers
Predicting temperature
What is the formula for Bayes’ theorem? Where (A & B) and (H & E) are events and P(B), P(H) & P(E) ≠ 0.
P(H|E) = [P(E|H) P(E)] / P(H)
P(A|B) = [P(A|B) * P(A)] / P(B)
P(H|E) = [P(H|E) P(H)] / P(E)
P(A|B) = [P(B|A) P(A)] / P(B)
In supervised learning, the training dataset consists of:
Only input features
Input features and corresponding labels
Only output labels
Randomly generated data
Which of the following is NOT a type of Machine Learning?
Supervised Learning
Unsupervised Learning
Reinforcement Learning
Data Cleaning
What is the purpose of cross-validation in machine learning?
To optimize hyperparameters
To increase the size of the training dataset
To evaluate the model's performance on unseen data
To reduce the dimensionality of the dataset
