Question 1

Which of the following can be used to impute data sets based only on information in the training set?
A)postprocess
B)preProcess
C)process
D)All of the Mentioned

Accepted Answer

The correct answer is B) preProcess. The preProcess function in data analysis is specifically designed to prepare data for further analysis, which includes imputing missing values based on the information available in the training set. This ensures that the model is not biased by information from the test set, maintaining the integrity of the model's predictive capability.

Question 2

Which of the following model model include a backwards elimination feature selection routine?
A)MCV
B)MARS
C)MCRS
D)All of the Mentioned

Accepted Answer

MARS (Multivariate Adaptive Regression Splines) includes a feature of backwards elimination in its algorithm to improve the model by removing less significant variables after initially considering a larger set of variables.

Question 3

Which of the following is a categorical outcome?
A)RMSE
B)RSquared
C)Accuracy
D)All of the Mentioned

Accepted Answer

Accuracy is a categorical outcome because it measures the proportion of correct predictions in classification problems, which deal with categories or classes. RMSE (Root Mean Square Error) and R^2 (R Squared) are numerical outcomes used in regression analysis, not categorical outcomes.

Question 4

Which of the following function provides unsupervised prediction ?
A)cl_forecast
B)cl_nowcast
C)cl_precast
D)None of the Mentioned

Accepted Answer

The functions listed (cl_forecast, cl_nowcast, cl_precast) do not inherently describe a method of unsupervised prediction in the context of machine learning or statistical analysis. Unsupervised prediction typically involves methods like clustering or dimensionality reduction, which are not explicitly mentioned in the options provided.

Question 5

What is true about Machine Learning?
A)Machine Learning (ML) is that field of computer science
B)ML is a type of artificial intelligence that extract patterns out of raw data by using an algorithm or method.
C)The main focus of ML is to allow computer systems learn from experience without being explicitly programmed or human intervention.
D)All of the above

Accepted Answer

Machine Learning encompasses all the statements provided: it is a field of computer science (A), it involves extracting patterns from raw data using algorithms (B), and its focus is on enabling computer systems to learn from experience without being explicitly programmed or requiring human intervention (C).

Question 6

ML is a field of AI consisting of learning algorithms that?
A)Improve their performance
B)At executing some task
C)Over time with experience
D)All of the above

Accepted Answer

Machine Learning (ML) is a subset of artificial intelligence (AI) that focuses on building systems that learn from and make decisions based on data. These systems improve their performance at executing tasks over time with experience, making all of the options (A, B, and C) correct.

Question 7

p ? 0q is not a?
A)hack clause
B)horn clause
C)structural clause
D)system clause

Accepted Answer

A Horn clause is a clause (a disjunction of literals) with at most one positive literal. The expression "p ? 0q" does not fit the definition of a Horn clause, as it does not represent a disjunction of literals in the context provided.

Question 8

The action _______ of a robot arm specify to Place block A on block B.
A)STACK(A,B)
B)LIST(A,B)
C)QUEUE(A,B)
D)ARRAY(A,B)

Accepted Answer

The action "STACK(A,B)" correctly specifies the action of placing block A on top of block B, mimicking the physical action of stacking objects in the real world.

Question 9

A__________ begins by hypothesizing a sentence (the symbol S) and successively predicting lower level constituents until individual preterminal symbols are written.
A)bottow-up parser
B)top parser
C)top-down parser
D)bottom parser

Accepted Answer

A top-down parser begins with the highest level symbol and works its way down to the individual components, predicting lower level constituents based on the initial hypothesis.

Question 10

A model of language consists of the categories which does not include ________.
A)System Unit
B)structural units.
C)data units
D)empirical units

Accepted Answer

The answer of A model of language consists of the...

Question 11

Different learning methods does not include?
A)Introduction
B)Analogy
C)Deduction
D)Memorization

Accepted Answer

"Introduction" is not a learning method in the context typically discussed in educational psychology or pedagogy. Learning methods such as analogy, deduction, and memorization are specific strategies or processes through which learning occurs. Introduction, however, generally refers to the initial part of a lesson or presentation where the topic or subject is presented but is not a method of learning in itself.

Question 12

The model will be trained with data in one single batch is known as ?
A)Batch learning
B)Offline learning
C)Both A and B
D)None of the above

Accepted Answer

Batch learning and offline learning both refer to the process where the model is trained with the entire dataset in one single batch, without the need for incremental or online updates.

Question 13

Which of the following are ML methods?
A)based on human supervision
B)supervised Learning
C)semi-reinforcement Learning
D)All of the above

Accepted Answer

The answer of Which of the following are ML methods?
A)based...

Question 14

In Model based learning methods, an iterative process takes place on the ML models that are built based on various model parameters, called ?
A)mini-batches
B)optimizedparameters
C)hyperparameters
D)superparameters

Accepted Answer

Hyperparameters are the model parameters that are set before the learning process begins and are used to control the learning process or the structure of the machine learning model itself. They are not learned from the data but are set prior to the training process and can significantly affect the performance of the model. Examples include learning rate, number of hidden layers, and batch size in neural networks.

Question 15

Which of the following is a widely used and effective machine learning algorithm based on the idea of bagging?
A)Decision Tree
B)Regression
C)Classification
D)Random Forest

Accepted Answer

Random Forest is a widely used and effective machine learning algorithm based on the idea of bagging, which involves creating multiple decision trees and combining their predictions to improve accuracy.

Question 16

To find the minimum or the maximum of a function, we set the gradient to zero because:
A)The value of the gradient at extrema of a function is always zero
B)Depends on the type of problem
C)Both A and B
D)None of the above

Accepted Answer

The value of the gradient at the extrema (minimum or maximum points) of a function is always zero because at these points, the slope of the tangent to the curve is horizontal, indicating no change in the function's value, which mathematically translates to a zero gradient.

Question 17

Which of the following is a disadvantage of decision trees?
A)Factor analysis
B)Decision trees are robust to outliers
C)Decision trees are prone to be overfit
D)None of the above

Accepted Answer

Decision trees can easily overfit the data, especially if they are not pruned properly or if the data is complex and noisy. This means they can perform very well on the training data but poorly on unseen data.

Question 18

How do you handle missing or corrupted data in a dataset?
A)Drop missing rows or columns
B)Replace missing values with mean/median/mode
C)Assign a unique category to missing values
D)All of the above

Accepted Answer

All of the options (A, B, C) are valid methods for handling missing or corrupted data in a dataset, depending on the specific circumstances and requirements of the analysis.

Question 19

When performing regression or classification, which of the following is the correct way to preprocess the data?
A)Normalize the data -> PCA -> training
B)PCA -> normalize PCA output -> training
C)Normalize the data -> PCA -> normalize PCA output -> training
D)None of the above

Accepted Answer

Normalizing the data before applying PCA ensures that each feature contributes equally to the analysis, which is important for PCA to work effectively.

Question 20

Which of the following statements about regularization is not correct?
A)Using too large a value of lambda can cause your hypothesis to underfit the data.
B)Using too large a value of lambda can cause your hypothesis to overfit the data
C)Using a very large value of lambda cannot hurt the performance of your hypothesis.
D)None of the above

Accepted Answer

The answer of Which of the following statements about regularization...

Quiz 3: Machine Learning and Data Analysis

Which of the following can be used to impute data sets based only on information in the training set?

Which of the following model model include a backwards elimination feature selection routine?

Which of the following is a categorical outcome?

Which of the following function provides unsupervised prediction ?

What is true about Machine Learning?

ML is a field of AI consisting of learning algorithms that?

p ? 0q is not a?

The action _______ of a robot arm specify to Place block A on block B.

A__________ begins by hypothesizing a sentence (the symbol S) and successively predicting lower level constituents until individual preterminal symbols are written.

A model of language consists of the categories which does not include ________.

Different learning methods does not include?

The model will be trained with data in one single batch is known as ?

Which of the following are ML methods?

In Model based learning methods, an iterative process takes place on the ML models that are built based on various model parameters, called ?

Which of the following is a widely used and effective machine learning algorithm based on the idea of bagging?

To find the minimum or the maximum of a function, we set the gradient to zero because:

Which of the following is a disadvantage of decision trees?

How do you handle missing or corrupted data in a dataset?

When performing regression or classification, which of the following is the correct way to preprocess the data?

Which of the following statements about regularization is not correct?