Elance Data Mining Test Answers 2015
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Which industry can benefit from data mining?
All of these
Retail
Manufacturing
Finance/Banking
A function used by a node in a neural net to
transform input data from any domain of values into a finite range of values is
known as a(n):
Confusion matrix
Activation Function
Chi-square
Antecedent
Changes to parts of a code could lead to the
problem of ______________ data.
granular
inconsistent
nonintegrated
dirty
What is data visualization?
A structured and developed prediction of data
results
The visual interpretation of complex relationships
in multidimensional data
The technical term for the act of data being stored
in a server
Decision trees are able to handle missing
values without using any impute transformation. True or False?
True
False
Data items grouped into relationships and
preferences are known as:
Punctional Organizations
Predictable Sets
Degrees of Fit
Clusters
Which of the following is valid XML?
All are valid
<valid>This One</valid>
<valid>"This One"</valid>
<body answer="valid">This
One</body>
A(n) _____ algorithm creates rules that
describe how often events have occurred together.
associative
artificial
pruning
CHAID
What are decision trees?
Complex reports generated by a qualified data
scientist
Structures that generate rules for the
classification of a dataset
Hierarchical dimensions that can be created with a
hyper cube browser
Data not collected by the organization, such as
data available from a reference book
Which of the following is not a relational
database?
Google Big Table
MongoDB
All of the above
Apache Cassandra
In predictive models, the values or classes to
be predicted are called the:
Response
Target variables
Dependent
All of these
In a neural net, to what does topology refer?
The number of layers and the number of nodes in
each layer
The graphical visualization of the data
The range of variables in a set
The number of nodes utilized
You are a credit risk manager of a retail
bank. Some information about customers are available to analytics. Based on
this data you have to decide that a person will be a good or bad customer.
Choose the appropriate data mining task for this business problems.
Segmentation
Classification
Regression
Which of the following clustering algorithms
can find clusters of arbitrary shape?
None of these
Single-Link
DSBSCAN
Both of these
True of False? Loose coupling data mining
architecture is mainly for memory-based data mining systems that does not
require high scalability and high performance.
True
False
What is CRISP-DM?
Microsoft's linear regression algorithm
A decision tree developed in the 1980's but almost
entirely replaced by the CART method today
A six phase method for predicting e-commerce buying
habits
A cross-industry standard process for data mining
The annual revenue of an international company
is correlated with other attributes like advertisement, exchange rate, inflation
rate etc. Having these values (or their reliable estimations for the next year)
the company have to calculate its expected revenue for the next year. Choose
the appropriate data mining task for this business problem.
Regression
Classification
Segmentation
Which of these are NOT considered internal
data factors?
Product Positioning
Economic downturns
Staff Skills
Price
With which of these layers does a neural
network start?
Transparent layer
Output Layer
Hidden Layer
Input layer
What is the measure of how much two random
variables change together?
covariance
stochastic inertia
polyconvergence
binary standard deviation
A hyperplane is a
decision boundary separating classes of data
non-terminating error condition
collection of linked hypertext files
variant of the C4.5 algorithm
Suppose that the company's marketing
department collects data from customers. Make customer groups to ensure that
the most appropriate group to target the different offers. Choose the
appropriate data mining task for this business problem.
Classification
Regression
Segmentation
The level of the model that specifies (often
graphically) which variables are locally dependent on each other.
Qualitative Level
Structural Level
Primary Level
Quantitative Level
To increase the confidence of your state of
classification performance on the entire population, you should:
Decrease the size of the training dataset
Increase the size of the test dataset
Decrease the size of the test dataset
Increase the size of the training dataset
Data not collected by the organization, such
as data from a proprietary database, that is combined with the organization’s
own data is known as:
Noise
Non-applicable date
Overlay
Overfitting
Which data mining technique organizes sets of
data into predefined groups?
Classification
Sequential Patterning
Clustering
Gamification
What is the front end layer of data mining
architecture?
Firewalls established to protect data from
malicious sources
The team of programmers who designed the software
utilized in a particular mining project
An intuitive and user friendly user interface
The hardware designed specifically for storage of
massive amounts of data
Which of these is an example of a sequential
pattern relationship?
Using business experience and gut instinct to
design a new floorplan in a grocery store
Reorganizing your basketball team's starting lineup
based on an analysis of performance
Placing two frequently purchased items next to each
other on the shelf
Predicting the likelihood of a backpack being
purchased based on a consumer's purchase of sleeping bags and hiking shoes
In the analysis of time-series data, the mean
value over a given time period (usually some interval in the past up to the
present) is called a(n)
unbiased mean
compounded mean
partial average
moving average
True or False? Tests in CART are always
Binary.
False
True
In the association between two variables, what
is the difference between the antecedent and the consequent?
The antecedent is on the left, the consequent on
the right
Nothing, they are interchangeable
The antecedent is on the right, the consequent is
on the left.
The antecedent is always a very complex variable
The algorithm powering the Google search
engine is:
The Brin-Page Method
PageRank
GoogleCrawler
AdaBoost
What is Dependency Modeling?
A task which consists of techniques for estimating,
from data, the joint multi-variate probability density function of all of the
variables/fields in the database.
Learning a function that maps a data item into one
of several predefined groups or clusters.
A multi-step process involving data preparation,
pattern searching, knowledge evaluation, and refinement with iteration after
modification.
The process of finding a model which describes
significant dependencies between variables
What is Regression?
Learning a function that maps a data item to a
real-valued prediction variable.
A descriptive task where one seeks to identify a
finite set of categories to describe the data.
An expression E in a language L describing facts in
a subset FE of F.
Learning a function that maps a data item into one
of several predefined groups.
What is Change and Deviation Detection?
A task focusing on discovering the most significant
changes in the data from previously measured or normative values
The process of finding a model which describes
significant dependencies between variables
A task which consists of techniques for estimating,
from data, the joint multi-variate probability density function of all of the
variables/fields in the database.
Methods for finding a compact description for a
subset of data.
Sharding refers to:
a measure of the noise in a database's contents
none of the above
simultaneously accessing multiple object databases
over SSH
partioning a database for distribution across
different servers
Which of these is NOT a common descriptions of
layers?
Functional
Output
Hidden
Input
What is the type of data mining that drives
the Amazon.com recommendation system?
Clustering Algorithms
Anomaly Detection
Association Learning
Fuzzy Logic
Support Vector Machines have an advantage over
Neural Networks because SVM's are
parametric
easier to train via online learning
none of the above
more resistent to local minima convergence
True or False? Economic indicators are
external data factors.
False
True
Which of these are NOT types of analytical
software:
Neural network
Machine learning
All are valid types
Statistical
Which of the following algorithms is generally
suitable for unsupervised learning tasks?
k-nearest neighbor
info-fuzzy networks
k-means algorithm
Restricted Boltzmann machine
Which of the following storage solutions is
most appropriate for a semi-structured dataset whose members do not all have
the same attributes?
MariaDB
SQLite
MySQL
MongoDB
In order to estimate classification
performance on an entire population, you need _______
(None of these)
disjoint training and test datasets
Test Datasets
Disjoint training
What is the extraction of useful if-then rules
from data based on statistical significance?
Preliminary Method Mapping
Dynamic Information Inference
Fuzzy Logic Application
Rule Induction
What is a KDD Process?
K-mean Data Discovery
Knoop-hardness measured through high-impact
dimension
Differential Decryption
Knowledge Discovery in Databases
Generalization error is a consequence of
Overfit
Underfit
Poorly defined Chernoff Bound
Parametric analysis
Which of the following is NOT a common source
system?
DB Connect
UDC
SAP source
Node
Which of these are evolutionary computational
methods?
Clustering algorithms
Bayesian inference algorithms
Genetic algorithms
Heuristic algorithms
True or False? The MARS algorithm cannot
produce rules.
True
False
A technique that classifies each record in a
dataset based on a combination of the classes of the k record(s) most similar
to it in a historical dataset is:
Nearest Neighbor
Decision Treeing
Logistic Regression
Association Model Query
Which of the following is most appropriate for
finding the shortest chain of friends linking two people in a social graph who
are not friends with each other?
Neural Networks
k-means algorithm
Dijkstra's algorithm
Markov chains
Which of the following is NOT a function of data
warehouses?
Extracting data
Cleaning data
Cleaning dirty data
Storing purchased data
What is Interestingness?
A discovered pattern that is true on new data with
some degree of certainty, and generalizes to other data.
An overall measure of pattern value, combining
validity, novelty, usefulness, and simplicity.
An expression E in a language L describing facts in
a subset FE of F.
A multi-step process involving data preparation,
pattern searching, knowledge evaluation, and refinement with iteration after
modification.
What is a genetic algorithm?
A classic algorithm for frequent item set mining
and association rule learning over transactional databases. It proceeds by
identifying the frequent individual items in the database and extending them to
larger and larger item sets as long as those item sets appear sufficiently
often in the database.
An algorithm that estimates how well a particular
pattern (a model and its parameters) meet the criteria of the KDD process.
Evaluation of predictive accuracy (validity) is based on cross validation.
Evaluation of descriptive quality involves predictive accuracy, novelty,
utility, and understandability of the fitted model. Both logical and
statistical criteria can be used for model evaluation.
A search algorithm that enables us to locate
optimal binary string by processing an initial random population of binary
strings by performing operations such as artificial mutation, crossover and
selection.
In the MapReduce model, Map and Reduce
functions act directly on which kind of data structure?
MySQL matrices
key-value pair
linked lists
relational databases
Which of the following is not a common goal of
the KDD Process:
Description
Performance
Prediction
Which of the following disciplines overlaps
Data Mining?
Artificial Intelligence
Statistics
All of the above
Linguistics
What is Classification?
Learning a function that maps a data item into one
of several predefined groups.
A descriptive task where one seeks to identify a
finite set of categories to describe the data.
Methods for finding a compact description for a
subset of data.
A discovered pattern that is true on new data with
some degree of certainty, and generalizes to other data.
Which of the followng clustering algorithms
can optimize an ojbective function?
DSBSCAN and Single Link
k-means only
k-means and CLARANS
Subspace Clustering Algorithms
What is Clustering?
Learning a function that maps a data item into one
of several predefined groups or clusters.
A descriptive task where one seeks to identify a finite
set of categories to describe the data.
A task which consists of techniques for estimating,
from data, the joint multi-variate probability density function of all of the
variables/fields in the database.
The process of finding a model which describes
significant dependencies between variables
Which of the following properties applies to
Single-Layer Perceptrons?
backpropagation
continuous output
random initalization of weights
able to learn non-linear separations
In Natural Language Processing, what is the
role of a lexical analyzer?
generates a context-free grammar
splits the stream of input characters into tokens
processes the parse tree for semantic meaning
checks the validity of a token
A DBMS reduces data redundancy and
inconsistency by
Enforcing referential integrity
Utilizing a data dictionary
Minimizing isolated files with repeated data
uncoupling program and data
In which type of analysis is a Kohonen feature
map typically employed?
Predictive analysis
Descriptive modeling analysis
Cluster analysis
Exploratory data analysis
Converted information to provide insights
about historical patterns and future trends is known as:
Meta-data
Clustering
Knowledge
Linear regression
What is Summarization?
A task focusing on discovering the most significant
changes in the data from previously measured or normative values
A descriptive task where one seeks to identify a
finite set of categories to describe the data.
The process of finding a model which describes
significant dependencies between variables
Methods for finding a compact description for a
subset of data.
Which of the following is NOT a method of
combining multiple models into an ensemble model?
Bootstrapping
Averaging
Stacking
Voting
"In 2% of the purchases at the hardware
store, both a pick and a shovel were bought,” is an example of:
Support
Topology
Supervised learning
Validation
Which of the following applications are
usually used to classify students' performances?
Regression analysis
If...then... analysis
Cluster analysis
Market-basket analysis
Which of the following properties is a
constraint on a RESTful application?
returns JSON output
stateful
linearly seperable
stateless
Which of the following algorithms produces
decision trees?
DBSCAN
ID3
logistic regression
none of the above
The component of the Hadoop Distributed
Filesystem responsible for storing metadata is called the
FS Shell
Datanode
Namenode
DFSAdmin
Which xpath selector expression captures all
link elements of the form 'http://example.com/profile/12345' in an html page
while excluding all links of the form 'http://example.com/casenumber/12345?
//href/profile
//a/profile
//a/[contains(@href, "profile")]/@href
//a/[contains(@href, "profile")]
What is Pig
A programming language that enables Hadoop to
operate as a data warehouse.
A programming language that simplifies the common
tasks of working with Hadoop.
None of these
If more than one value occurs the same number
of times, the data is:
Multi-leafed
Multi-modal
Multi-faceted
Multivariated
Taking multiple random samples of data and
building a classification model for each is known as:
Clustering
Boosting
Binning
Fuzzy Sampling
A commonly used continuous alternative to the
step function in multi-layered neural network output is the
logistic function
hyperbolic function
logarithmic function
multi-layered NN cannot compute continuous output
The authentication protocol used by many
significant web APIs is called:
SSL
PGP
OAuth
HTTPS
What is CURL?
A methodology for classifying hidden features of
data
The part of HTTP that specifies access permission
Combinatorial Unsupervised Recursive Learning
algorithm
A command-line tool for retrieving files
Apriori is a seminal algorithm for finding
frequent item sets using:
Candidate generation
Normal mixture models
None of these
Overfitting methods
What is the first step in the business
understanding phase?
Firmly grasp business objectives and needs
Create data mining goals to achieve the business
objectives
Create a list of all relevant algorithms to be
applied to the task
Assess the current situation by finding out the
resources, assumptions, constraints etc.
In any numerical data set with a meaningful
mean value, what is the minimum fraction of data that will fall within n
standard deviations of the mean?
1/n^2
1/n
1-1/n^2
1/2n
Which of these is a possible architecture of a
data mining system?
Transitive coupling
Magnetic coupling
No-coupling
Quickstart coupling
Which of these is not a step in the KDD
process?
Data Mining
Data Cleaning
Data Integration
Data Quantification
Which of the following method can be used for
modeling a categorical target variable?
Regression
Non-Linear Regression
All of the Above
ARIMA
Logistic Regression
The level of the model that specifies the
strengths of the dependencies using some numerical scale.
Quantitative Level
Numeric Level
Primary Level
Dependency Level
Which of the following is not a primary phase
of a Hadoop Reducer?
Reduce
Map
Sort
Shuffle
The measured differences between a model and
its predictions are known as:
Non-applicable data
Noise
Range
Outliers
True or False? Artificial neural networks are
linear predictive models.
False
True
Which are popular data mining methods?
Probabilistic Graphical Dependency Models
Decision Trees and Rules
Relational Learning Models
All of these
Which decision tree method performs
multi-level splits when computing classification trees?
ID3 (Iterative Dichotomiser 3)
CHAID (Chi Square Automatic Interaction Detection)
C4.5 algorithm
CART (Classification and Regression Trees)
What is the advantage of the k-Medoids
Clustering Algorithm over the k-Means Clustering (Lloyd's) Algorithm?
represents clusters by center
more resistant to outliers
all of the above
uses iterative refinement
Which of the following is not an appropriate tool
for harvesting data from a website that accesses its database through
Javascript/AJAX calls?
wget
PhantomJS
Selenium
All of the above are appropriate
Which of the following is part of a retail
customer data mining strategy?
loyalty cards
holiday sale
customer testimonials
money-back guarantee
Hash based technique, Transaction Reduction,
Portioning, Sampling, and Dynamic Item Counting are all examples of what?
Techniques to improve the efficiency of an Apriori
algorithm
Method to repeatedly scan the scan the database and
check a large set of candidates by pattern matching.
Methods of generating frequent item sets without
candidate generation.
Methods for finding a compact description for a
subset of data.
Which of the following is not valid JSON?
All are valid
{"answer": "this one"}
{["answer": "this one"]}
{"answer": ["this one"]}
The two major functions of BI servers are:
Management and delivery
Processing and management
Application and delivery
Source and results
How do you measure interestingness in
association patterns?
meaure accuracy
measure relevance
measure variance
measure lift
A descriptive approach to exploring data that
can help identify relationships among values in a database is:
Clustering
Predictive analysis
Link analysis
Function activation
Where can a website operator generally find
data on her customers' IP addresses?
cookies
all of the above
HTTP request headers
server logfiles
Data mining provides a link between:
Online analytical processing and dynamic
information
Genetic algorithms and logistic regression
Parallel processing and RAID
Separate transactional and analytical systems
What is Hive
Both of these
Hive is a programming language that simplifies the
common tasks of working with Hadoop.
Hive enables Hadoop to operate as a data warehouse.
What is the purpose of the Hadoop Distributed
File System (HDFS)?
Creating a context in which there are no
restrictions on the data, enabling it to be unstructured and schemaless.
To enable computation to take place by allowing
each server to have access to the data.
Ensuring that data is replicated with redundancy
across the cluster.
All of these.
The silhouette coefficient can be used to
determine the natural number of clusters for ________.
Hierarchichal Algorithms
Partitioning Algorithms
Density Based Algorithms
Subspace Clustering Algorithms
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