Computer Science · all questions

Machine Learning
practice.

Practice every MCQ with options. Use Show answers when you want the correct option and solution.

435

Questions

10/22

Page

Pick an option on a question to see the right answer and solution.

Q181

Lasso can be interpreted as least-squares linear regression where

Select an option to see the answer and solution.

Q182

Which of the following method is used to find the optimal features for cluster analysis

Select an option to see the answer and solution.

Q183

Perceptron Classifier is

Select an option to see the answer and solution.

Q184

The correlation coefficient for two real-valued attributes is -0.85. What does this value tell you?

Select an option to see the answer and solution.

Q185

There are also many univariate methods that can be used in order to select the best features according to specific criteria based on . . . . . . . .

Select an option to see the answer and solution.

Q186

Which of the following is an application of NN (Neural Network)?

Select an option to see the answer and solution.

Q187

Which statement is true about the K-Means algorithm?

Select an option to see the answer and solution.

Q188

which of the following step / assumption in regression modeling impacts the trade-off between under-fitting and over-fitting the most.

Select an option to see the answer and solution.

Q189

How can we best represent 'support' for the following association rule: "If X and Y, then Z".

Select an option to see the answer and solution.

Q190

With Bayes theorem the probability of hypothesis(H) specified by P(H) is referred to as

Select an option to see the answer and solution.

Q191

How can you avoid overfitting ?

Select an option to see the answer and solution.

Q192

What are the steps for using a gradient descent algorithm?
1. Calculate error between the actual value and the predicted value
2. Reiterate until you find the best weights of network
3. Pass an input through the network and get values from output layer
4. Initialize random weight and bias
5. Go to each neurons which contributes to the error and change its respective values to reduce the error

Select an option to see the answer and solution.

Q193

Problem in multi regression is ?

Select an option to see the answer and solution.

Q194

Tree/Rule based classification algorithms generate ... rule to perform the classification.

Select an option to see the answer and solution.

Q195

In the regression equation Y = 75.65 + 0.50X, the intercept is

Select an option to see the answer and solution.

Q196

there's a growing interest in pattern recognition and associative memories whose structure and functioning are similar to what happens in the neocortex. Such an approach also allows simpler algorithms called . . . . . . . .

Select an option to see the answer and solution.

Q197

We can also compute the coefficient of linear regression with the help of an analytical method called "Normal Equation". Which of the following is/are true about "Normal Equation"?
1. We don't have to choose the learning rate
2. It becomes slow when number of features is very large
3. No need to iterate

Select an option to see the answer and solution.

Q198

Bayes theorem describes the probability of an event, based on prior knowledge of conditions that might be related to the event.

Select an option to see the answer and solution.

Q199

if there is only a discrete number of possible outcomes (called categories), the process becomes a . . . . . . . .

Select an option to see the answer and solution.

Q200

Give the correct Answer for following statements. 1. It is important to perform feature normalization before using the Gaussian kernel. 2. The maximum value of the Gaussian kernel is 1.

Select an option to see the answer and solution.

Prev 8 9 10 11 12 Next