Machine Learning Set 21

Q1 | there's a growing interest in pattern recognition and associative memories whose structure and functioningare similar to what happens in the neocortex. Such an

Q2 |              showed better performance than other approaches, even without a context-based model

Q3 | Which of the following sentence is correct?

Q4 | What is ‘Overfitting’ in Machine learning?

Q5 | What is ‘Test set’?

Q6 | what is the function of ‘Supervised Learning’?

Q7 | Commons unsupervised applications include

Q8 | Reinforcement learning is particularly efficient when                             .

Q9 | During the last few years, many              algorithms have been applied to deepneural networks to learn the best policy for playing Atari video games and to teach an agent how to associate the right action with an input representingthe state.

Q10 | Common deep learning applications include         

Q11 | if there is only a discrete number of possible outcomes (called categories),the process becomes a            .

Q12 | 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?

Q13 | Which of the following sentence is FALSE regarding regression?

Q14 | scikit-learn also provides functions for creatingdummy datasets from scratch:

Q15 |           which can accept a NumPy RandomStategenerator or an integer seed.

Q16 | In many classification problems, the target dataset is made up of categorical labels which cannot immediately be processed by any algorithm. An encoding is needed and scikit-learn offers atleast          valid options

Q17 |             is the most drastic one and should be considered only when the dataset is quite large, the number of missing features is high, and any prediction could be risky.

Q18 | It's possible to specify if the scaling process must include both mean and standard deviation using theparameters                 .

Q19 | Which of the following selects the best K high-scorefeatures.

Q20 | Suppose you have fitted a complex regression model on a dataset. Now, you are using Ridge regression with tuning parameter lambda to reduce its complexity. Choose the option(s) below which describes relationship of bias andvariance with lambda.

Q21 | What is/are true about ridge regression?1. When lambda is 0, model works like linear regression model2. When lambda is 0, model doesn’t work like linear regression model3. When lambda goes to infinity, we get very, very small coefficients approaching 04. When lambda goes to infinity, we get very, very large coefficients approachinginfinity

Q22 | Which of the following method(s) does not haveclosed form solution for its coefficients?

Q23 | Function used for linear regression in R is

Q24 | In the mathematical Equation of Linear Regression Y = β1 + β2X + ϵ, (β1, β2) refers to                       

Q25 | Suppose that we have N independent variables (X1,X2… Xn) and dependent variable is Y. Now Imagine that you are applying linear regression by fitting the best fit line using least square error on this data. 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?