×
Detail Form
We will send your result on your email id and phone no. please fill detail
1.
Which of the following statement is true in following case?
2.
Which of the following is an example of a deterministic algorithm?
3.
A Pearson correlation between two variables is zero but, still their values can still be related to each other.
4.
Which of the following statement(s) is / are true for Gradient Decent (GD) and Stochastic Gradient Decent (SGD)?
1. In GD and SGD, you update a set of parameters in an iterative manner to minimize the error function.
2. In SGD, you have to run through all the samples in your training set for a single update of a parameter in each iteration.
3. In GD, you either use the entire data or a subset of training data to update a parameter in each iteration.
1. In GD and SGD, you update a set of parameters in an iterative manner to minimize the error function.
2. In SGD, you have to run through all the samples in your training set for a single update of a parameter in each iteration.
3. In GD, you either use the entire data or a subset of training data to update a parameter in each iteration.
5.
Which of the following hyper parameter(s), when increased may cause random forest to over fit the data?
1. Number of Trees
2. Depth of Tree
3. Learning Rate
1. Number of Trees
2. Depth of Tree
3. Learning Rate
6.
Imagine, you are working with
7.
Below are the 8 actual values of target variable in the train file.
[0,0,0,1,1,1,1,1]
What is the entropy of the target variable?
[0,0,0,1,1,1,1,1]
What is the entropy of the target variable?
8.
Let's say, you are working with categorical feature(s) and you have not looked at the distribution of the categorical variable in the test data. You want to apply one hot encoding (OHE) on the categorical feature(s). What challenges you may face if you have applied OHE on a categorical variable of train dataset?
9.
10.
Let's say, you are using activation function X in hidden layers of neural network. At a particular neuron for any given input, you get the output as