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Worksheets21CSC305P - Machnine Learning - Quiz
Total questions: 15
Worksheet time: 5mins
In Bayesian linear regression, the posterior distribution of the model parameters is computed by combining which of the following elements?
The likelihood of the data and a regularization term
The prior distribution of the parameters and a test set evaluation
The likelihood of the data and the prior distribution of the parameters
The posterior predictive distribution and the regularization term
Identify the problem:
We have information of all houses in a particular area like size, type and design of house, locality, colour, previous purchase etc. on the basis of these data we have to find the price of a particular house.
Classification
Regression
Clustering
Prbabilistic
Suppose you are dealing with 4 class classification problem and you want to train a SVM model on the data for that you are using One-vs-all method. Now, say for training 1 time in one vs all setting the SVM is taking 10 second. How many seconds would it require to train one-vs-all method end to end?
20
40
80
60
What is the purpose of the kernel trick in SVM?
To transform data into a higher-dimensional space
To reduce the dimensionality of data
To eliminate outliers from the dataset
To visualize data in 2D
What is a key feature of the Laplace approximation?
It is applicable to discrete variables only
It is used for linear regression only
It finds a Gaussian approximation to a probability density
It requires a large sample size
Which of the following kernels is NOT commonly used in SVM?
Linear Kernel
Polynomial Kernel
Radial Basis Function (RBF) Kernel
Sigmoid Kernel
Exponential Kernel
In SVM, what is the primary goal of maximizing the margin?
To minimize the error on the test set
To minimize the error on the training set
To make the model less sensitive to overfitting
To increase the complexity of the decision boundary
How does the k-Means algorithm determine convergence?
When the centroids stop moving significantly between iterations
When all data points are assigned to a cluster
After a fixed number of iterations
When the number of clusters equals 'k'
In a multivariate normal distribution, which of the following describes the relationship between the variables?
They are independent and identically distributed.
They can be correlated with each other.
They have equal variances.
They must be normally distributed individually.
___________ clustering seeks the minimum distance between any records in two clusters to find the distance between the points in two clusters.
Single linkage
Complete Linkage
Average Linkage
None
What is the purpose of pre-processing the data in PCA?
To make the data more comparable across attributes
To make the data less comparable
To discard the data
To make the data more complex
In Gaussian mixture model clustering, the number of Gaussian distribution functions used is equal to
Number of clusters
Number of attributes
Number of instances
Number of iterations
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
What is the purpose of the slack variable in the soft margin SVM?
To handle outliers and noise in the dataset
To reduce the dimensionality of the data
To increase the number of support vectors
To improve the speed of the algorithm
What is the main difference between Regression and Classification algorithms?
Regression algorithms are used to predict house prices, while Classification algorithms are used to predict weather.
Regression algorithms are used to predict weather, while Classification algorithms are used to predict house prices.
Regression algorithms are used to predict discrete values, while Classification algorithms are used to predict continuous values.
Regression algorithms are used to predict continuous values, while Classification algorithms are used to predict discrete values.
