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.

Identify a problem:

You have details of corona affected positive cases found in various regions. Depending upon parameters like number of increasing corona infected patients, weather conditions etc. regions are classified into red zone, Green zone and Orange Zone. On the basis of these data we have to predict the region of a city.

State whether True or False

The most meaningful and interpretable principal components are those that have the largest eigenvalues

Cross validation is used for

State True or False

For k cross-validation, larger k value implies more bias.

which of the following is not a method of cross validation?

If I am using all features of my dataset and I achieve 100% accuracy on my training set, but ~70% on validation set, what should I look out for?

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 (i.e., ) is 1.

Which is/are method to do multiclass classification?

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?

For evaluating regression models, which of the following metrics can not be used ?

Suppose that we have N independent variables (X1,X2… Xn) and dependent variable is Y. Now Imagine that you are applying linear regression.You found that correlation coefficient for one of it’s variable(Say X1) with Y is -0.95.

Which of the following is true for X1?

Suppose that you have a dataset D1 and you design a linear regression model of degree 3 polynomial and you found that the training and testing error is “0” or in another terms it perfectly fits the data.

What will happen when you fit degree 4 polynomial in linear regression?

Which of the following function is used by Logistic Regression to convert the probability in between [0,1]

Regarding Bias and Variance ,which of the following statement is True?

Which of the following is true about Lasso and Ridge Regression?

Identify Performance measure P from following Traffic Pattern Analysis Algorithm.

Select All prime reasons for using unsupervised Machine Learning Algorithms.

In k-mean algorithm, K stands for

Can Decision Tree be used for clustering?

Which clustering method takes care of variance in data?

Which clustering method takes care of oblong dataset?

Does k-mean algorithm always converge?

Is Gaussian mixture model supervised?

Is k-mean clustering supervised?

Is Gaussian mixture model Probabilistic?

In Gaussian mixture model clustering, the number of Gaussian distribution functions used is equal to

Which among the following is not true for a Bayesian classifier?

What type of Machine Learning Algorithm is suitable for predicting the continuous dependent variable?

What type of Machine Learning Algorithm is suitable for predicting the dependent variable with two different values?

The correlation in between mobile usage and exam score of a person found to be -2.2. What is your inference from the above statement.

The residual is the difference in between ________________

Suitable evaluation metric for measuring the performance of a given regression model is

If we decrease the input variable by one unit in a simple linear regression model. How many units of the output variable will change?

Appropriate chart for visualizing the linear relationship between two variables is _________________

The Number of coefficients required to estimate a simple linear regression?

KNN Algorithm can be used for

KNN is ___________ algorithm

What kind of distance metric(s) are suitable for categorical variables to finding the closest neighbors

What kind of distance metric(s) are suitable for continuous variables to find the closest neighbors

KNN algorithm appropriate for

KNN algorithm requires

The entropy of a given dataset is zero. This statement implies what?

If the given dataset contains 100 observations out of 50 belongs to class1 and other 50 belongs to class2. What will be the entropy of the given dataset?

How do you choose the root node while constructing a Decision Tree?

Chose the correct criterion for Decision Tree Classifier in sklearn package

In a Decision Tree Leaf Node represents_____________

Consider the above Confusion Matrix of a classifier and choose the correct statements

Which of the following methods is used for feature selection in machine learning?