Exam 2 Review Questions

A hidden layer is _________. A) A layer in a neural network between the input and outputs. B) A layer in social media networks that is hidden to the user. C) A layer in streaming stacks that processes data while remaining hidden to users. D) None of the above.

A) A layer in a neural network between the input and outputs.

Which one defines how to pass the value from inputs through the neuron and make the output? A) Activation function B) Value function C) Control function D) Transform function

A) Activation function

Convolutional neural networks are most notably used for __________. A) image classification B) social network analytics C) forecasting the stock market D) none of these

A) image classification

Assume you want to perform supervised learning and to predict number of newborns according to size of storks' population, it is an example of _______ A) Classification B) Regression C) Clustering D) Structural equation modeling

B) Regression

The goal of which task is to predict categories? _______ A) Regression B) Clustering C) Classification D) Association analysis

C) Classification

Select the incorrect statement about prediction that is one of data mining tasks? A) Two major types of predictions are classification and regression. B) Supervised learning methods can be used for classification and regression. C) Classification is used for predicting continuous outcome variables. D) Regression is used for predicting continuous outcome variables.

C) Classification is used for predicting continuous outcome variables.

Which of the following is not true regarding data mining? _______ A) It focuses on discovering useful information. B) It can use machine learning techniques. C) It is one task within a process. D) It is a process from start to end.

C) It is one task within a process.

( ) is a subset of machine learning that uses multi-layered artificial neural networks.

Deep learning

(_______) is a industry standard data mining process that is iterative in nature and has 6 steps. A) CRISP-DM B) SEMMA C) KDD

A) CRISP-DM

(_______) is a task to segment data into groups that are not previously defined. A) Clustering B) Classification

A) Clustering

Task of inferring a model from labeled training data is called ________ A) Supervised learning B) Unsupervised learning

A) Supervised learning

Data mining is defined as a process of identifying valid, novel, potentially useful, and understandable patterns in data. What is the meaning of 'valid'? A) The pattern should hold true on new data. B) It can use machine learning techniques. C) The pattern is easy to understand. D) The discovered patterns should lead to benefits.

A) The pattern should hold true on new data.

What is the confidence level of the association rule [Cereal -> Milk] in this data? _______ A) 0.65 B) 0.75 C) 1.0 D) 0.57 1. Cereal, Milk, Bread 2. Eggs, Cereal, Beer, Water 3. Milk, Water, Cereal 4. Eggs, Beer, Bread 5. Cereal, Milk, Bread

B) 0.75

Which of the following is an example of unsupervised learning? _______ A) Classification B) Clustering C) Regression D) None of those

B) Clustering

(_______) is one of the three numeric measures that must be considered for an association rule; it measures its predictive power. A) Support B) Confidence C) Lift D) Precision

B) Confidence

(_______) is one of CRISP-DM phases. This phase includes several tasks, such as data cleansing and transforming. A) Data consolidation B) Data preparation C) Model evaluation D) Data collection

B) Data preparation

Which of the following is used for clustering? A) Logistic regression B) K-means C) Apriori D) Neural networks

B) K-means

Regression works by: A) Maximizing the distance between each data point in the dataset and the regression model. B) Minimizing the distance between each data point in the dataset and the regression model.

B) Minimizing the distance between each data point in the dataset and the regression model.

Let's suppose that a retailer found an association rule (Peanut butter à Bread) in their database. This rule's confidence is 0.7, support is 1.0, and lift is 0.85. Select the incorrect statement: _______ A) The right-hand side of this association rule is called the result. B) The retailer can think that those two items are truly associated. C) A purchase involving peanut butter is accompanied by a purchase of bread 70% of the time. D) Every transaction in the database includes the two items.

B) The retailer can think that those two items are truly associated.

Association Analysis is a/an _________. A) Supervised learning B) Unsupervised learning C) Reinforcement learning

B) Unsupervised learning

What is the problem of finding hidden structure in data without given an explicit output variable (unlabeled data)? A) Supervised learning B) Unsupervised learning

B) Unsupervised learning

What is the first phase of CRISP-DM process? A) Data understanding B) Data collection C) Business understanding D) Modeling building

C) Business understanding

CRISP-DM stands for ________________________________________________

Cross-Industry Standard Process for Data Mining

What are the major data mining tasks? A) Prediction B) Association C) Cluster D) All of them

D) All of them

The goal of k-means algorithms is to maximize the within-cluster-variation. (True / False)

False

The support levels of the two association rules, [A -> B] and [B -> A], are different. (True / False)

False

( ) is the scientific study of statistical models that computer systems use to perform a specific task without using explicit instructions.

Machine learning

Discriminating between spam and non-spam emails is a classification task (True / False)

True

The support vector classifier allows some observations to be on the incorrect side of the separate line. (True / False)

True