Machine Learning — Part 2 MCQs with Explanations

removing columns which have too many missing values is the correct answer to “Which of the following techniques would perform better for reducing dimensions of a data set”. This question is standard in competitive examination syllabi for Machine Learning.

Semi-supervised is the correct answer to “. . . . . . . . can be adopted when it's necessary to categorize a large amount of data with a few complete examples or when there's the need to impose some constraints to a clustering algorithm.”. This question is standard in competitive examination syllabi for Machine Learning.

TRUE is the correct answer to “Binarize parameter in BernoulliNB scikit sets threshold for binarizing of sample features.”. This question is standard in competitive examination syllabi for Machine Learning.

transform data to zero mean is the correct answer to “What would you do in PCA to get the same projection as SVD”. This question is standard in competitive examination syllabi for Machine Learning.

dimension is the correct answer to “The . . . . . . . . of the hyperplane depends upon the number of features.”. This question is standard in competitive examination syllabi for Machine Learning.

greedy is the correct answer to “What is the approach of basic algorithm for decision tree induction”. This question is standard in competitive examination syllabi for Machine Learning.

Yes is the correct answer to “Can we extract knowledge without apply feature selection”. This question is standard in competitive examination syllabi for Machine Learning.

0.06 is the correct answer to “Suppose there are 25 base classifiers. Each classifier has error rates of e = 0.35. Suppose you are using averaging as ensemble technique. What will be the probabilities that ensemble of above 25 classifiers will make a wrong prediction? Note: All classifiers are independent of each other”. This question is standard in competitive examination syllabi for Machine Learning.

TRUE is the correct answer to “When the number of classes is large Gini index is not a good choice.”. This question is standard in competitive examination syllabi for Machine Learning.

training data is the correct answer to “Data used to build a data mining model.”. This question is standard in competitive examination syllabi for Machine Learning.

logistic regression is the correct answer to “This technique associates a conditional probability value with each data instance.”. This question is standard in competitive examination syllabi for Machine Learning.

to transform the data from nonlinearly separable to linearly separable is the correct answer to “What is the purpose of the Kernel Trick”. This question is standard in competitive examination syllabi for Machine Learning.

true - perceptrons can do this but are unable to learn to do it - they have to be explicitly hand-coded is the correct answer to “Having multiple perceptrons can actually solve the XOR problem satisfactorily: this is because each perceptron can partition off a linear part of the space itself, and they can then combine their results.”. This question is standard in competitive examination syllabi for Machine Learning.

FALSE is the correct answer to “Can we calculate the skewness of variables based on mean and median”. This question is standard in competitive examination syllabi for Machine Learning.

TRUE is the correct answer to “It is possible to design a Linear regression algorithm using a neural network”. This question is standard in competitive examination syllabi for Machine Learning.

Couldn't comment on Test error is the correct answer to “If Linear regression model perfectly first i.e., train error is zero, then . . . . . . . .”. This question is standard in competitive examination syllabi for Machine Learning.

FALSE is the correct answer to “Increase in size of a convolutional kernel would necessarily increase the performance of a convolutional network.”. This question is standard in competitive examination syllabi for Machine Learning.

a and b is the correct answer to “To control the size of the tree, we need to control the number of regions. One approach to do this would be to split tree nodes only if the resultant decrease in the sum of squares error exceeds some threshold. For the described method, which among the following are true? a. It would, in general, help restrict the size of the trees b. It has the potential to affect the performance of the resultant regression/classification model c. It is computationally infeasible”. This question is standard in competitive examination syllabi for Machine Learning.

none of these is the correct answer to “Which of the following is the difference between stacking and blending”. This question is standard in competitive examination syllabi for Machine Learning.

nonlinear, binary is the correct answer to “Logistic regression is a . . . . . . . . regression technique that is used to model data having a . . . . . . . . outcome.”. This question is standard in competitive examination syllabi for Machine Learning.

forward feature selection is the correct answer to “In following type of feature selection method we start with empty feature set”. This question is standard in competitive examination syllabi for Machine Learning.

linear functions is the correct answer to “Neural Networks are complex . . . . . . . . with many parameters.”. This question is standard in competitive examination syllabi for Machine Learning.

missing_values is the correct answer to “How it's possible to use a different placeholder through the parameter . . . . . . . .”. This question is standard in competitive examination syllabi for Machine Learning.

branch of bank is the correct answer to “Which of the following is a categorical data”. This question is standard in competitive examination syllabi for Machine Learning.

Option "considers the reduction in error when moving from the reduced model to the complete model" is the correct answer for this question under Machine Learning.

TRUE is the correct answer to “Linear Regression is a supervised machine learning algorithm.”. This question is standard in competitive examination syllabi for Machine Learning.

Spam detection, Pattern detection, Natural Language Processing is the correct answer to “Which of the following are supervised learning applications”. This question is standard in competitive examination syllabi for Machine Learning.

both A and B is the correct answer to “Which of the following is a good test dataset characteristic”. This question is standard in competitive examination syllabi for Machine Learning.

independent is the correct answer to “Features being classified is . . . . . . . . of each other in Nave Bayes Classifier”. This question is standard in competitive examination syllabi for Machine Learning.

FALSE is the correct answer to “The gini index is not biased towards multivalued attributed.”. This question is standard in competitive examination syllabi for Machine Learning.

k-means clustering is the correct answer to “This unsupervised clustering algorithm terminates when mean values computed for the current iteration of the algorithm are identical to the computed mean values for the previous iteration.”. This question is standard in competitive examination syllabi for Machine Learning.

Vector is the correct answer to “In syntax of linear model lm(formula,data,..), data refers to . . . . . . . .”. This question is standard in competitive examination syllabi for Machine Learning.

k-means clustering is the correct answer to “This clustering algorithm terminates when mean values computed for the current iteration of the algorithm are identical to the computed mean values for the previous iteration Select one:”. This question is standard in competitive examination syllabi for Machine Learning.

Imputer is the correct answer to “scikit-learn offers the class. . . . . . . ., which is responsible for filling the holes using a strategy based on the mean, median, or frequency”. This question is standard in competitive examination syllabi for Machine Learning.

none of the mentioned is the correct answer to “Which of the following function provides unsupervised prediction”. This question is standard in competitive examination syllabi for Machine Learning.

Deep learning is the correct answer to “In the last decade, many researchers started training bigger and bigger models, built with several different layers that's why this approach is called . . . . . . . .”. This question is standard in competitive examination syllabi for Machine Learning.

1 and 2 is the correct answer to “Which of the following statement(s) can be true post adding a variable in a linear regression model? 1. R-Squared and Adjusted R-squared both increase 2. R-Squared increases and Adjusted R-squared decreases 3. R-Squared decreases and Adjusted R-squared decreases 4. R-Squared decreases and Adjusted R-squared increases”. This question is standard in competitive examination syllabi for Machine Learning.

it can be used in both classification and regression is the correct answer to “Which of the following option is true about k-NN algorithm”. This question is standard in competitive examination syllabi for Machine Learning.

both a and b is the correct answer to “Feature can be used as a”. This question is standard in competitive examination syllabi for Machine Learning.

mean positive error is the correct answer to “The average positive difference between computed and desired outcome values.”. This question is standard in competitive examination syllabi for Machine Learning.