Predictive Analytics Modeler Explorer Award Update
Predictive Analytics Modeler Explorer Award update
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Predictive Analytics Modeler Explorer Award updated 2023 Questions and Answers with complete solution
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Predictive Analytics Modeler Explorer Award Update
Predictive Analytics Modeler Explorer Award updated 2023 Questions and Answers with complete solution
Which statement describes the goal of a typical data mining project?
A. Produce reports describing customer behavior, based on empirical data.
B. Assess risk associated with past busines...
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Predictive Analytics Modeler Explorer Award updated
2023 Questions and Answers with complete solution
Which statement describes the goal of a typical data mining project?
A. Produce reports describing customer behavior, based on empirical data.
B. Assess risk associated with past business decisions.
C. Predict the behavior of future cases based on past information.
D. Provide insightful financial reports that help business decision making.
C. Predict the behavior of future cases based on past information
Which tab allows you to count how many valid records exist in the data audit
node dialog?
A. Annotations
B. Output
C. Settings
D. Quality
D. Quality
You need to create a single report that can be run at different times for different
months without editing the stream after it has been deployed. How should you
build the stream?
A. Make a filler node to put the correct value into the stream.
B. Create a session parameter for the month. Enter the data as needed.
C. Hard code the month in a SuperNode. Update when necessary.
D. Use a partition node to create separate sample groups for each month.
B. Create a session parameter for the month. Enter the data as needed.
What is a segmentation modeling method that automatically sets the number of
clusters into which records are then classified?
A. Kohonen networks
B. AutoCluster
C. TwoStep
D. K-Means
C. TwoStep
Identify an important characteristic of the segmentation model.
A. The segmentation model identifies clusters in the data.
B. The segmentation model does not create a nugget.
C. The segmentation model has multiple targets.
D. The segmentation model has a predefined output.
A. The segmentation model identifies clusters in the data.
You are building a stream with SPSS MODELER. The bottom of the Table output
window shows many records with all $null$ values. How can you eliminate these
records from your model?
,A. Edit the properties of the stream and choose the option: "Exclude null values".
B. Generate a Select node where data_known="yes".
C. Edit the Table node and choose the option: "Exclude null values".
D. Edit the Select node and add "where data_known="yes" to the SQL statement.
B. Generate a Select node where data_known="yes".
How do you specify which records are grouped together in a derive node in count
mode?
A. by entering a 'Reset when' criteria
B. by entering an 'Increment by' of 0
C. by entering an 'Initial value' of the field name
D. by entering the 'Group by' field
A. by entering a 'Reset when' criteria
You have built a stream in SPSS MODELER that includes two source nodes and
four output nodes. How can you run the stream to produce all four outputs?
A. Click the Run button from the main menu.
B. Right-click a source node and choose Run "Selection".
C. Right-click one of the terminal nodes and choose Run All".
D. Select a source node and click the Run button from the main menu.
A. Click the Run button from the main menu.
Which selection is indicative of a Association modeling objective?
A. A person's age is a determining factor to predict whether a Website visitor will
click on an ad for something interesting on Facebook.
B. Subjects who change jobs every six months are more likely to default on an
automobile loan.
C. Income is a determining factor for whether a family takes a summer vacation to
a foreign country or resort area.
D. Cell phone users who subscribe to plan A will likely purchase the newest cell
phone as soon as it is released.
D. Cell phone users who subscribe to plan A will likely purchase the newest cell phone
as soon as it is released.
Which of the following means a model can fit the training set perfectly and fails
with unseen future data?
A. Underfitting
B. Prediction
C. Overfitting
D. Cross validation
C. Overfitting
You are using Data Refinery, which tab can give you insights into your data,
helping you identify patterns, connections, and relationships?
A. Functions
B. Profile
C. Operations
D. Visualizations
D. Visualizations
, Which node will create a classification table, based on the accuracy of a model?
A. Sample
B. Analysis
C. Partition
D. Data Audit
B. Analysis
Your Data Set consists of 5000 records describing houses and you are trying to
predict the house price, if one of the fields in your data set describes the area of
the house, what should the role of this field be?
A. Both
B. Partition
C. Target
D. Input
D. Input
Which statement describes a CHAID analysis?
A. the process of Detecting Automatic Interaction through classification and
heuristics
B. a classification and prediction method based on classification and regression
C. a decision-tree technique that looks for predictive variables based on Chi-
square testing
D. a modified Chi-square analysis that produces a predictive decision tree
C. a decision-tree technique that looks for predictive variables based on Chi-square
testing
Which of the following can't be a reason for a data mining project failure?
A. Not enough time spent on data preparation
B. The complexity of the model is of O(n2)
C. Bad quality data
D. Some inputs/factors can't be legally used
B. The complexity of the model is of O(n2)
Which of the following means a machine learning model cannot fit the training
data or generalize to new data?
A. Overfitting
B. Feedforwad
C. Underfitting
D. Backpropagation
C. Underfitting
Which statement is true about Apache Spark?
A. Apache Spark is a service with features for training and deploying machine
learning models and neural networks.
B. Apache Spark is an open source distributed cluster computing framework
optimized for extremely fast and large scale data processing.
C. Apache Spark is a collaborative platform for data scientists that is built on
open source components and IBM added value, and is available in the cloud or
on-premises.
D. Apache Spark is a collaborative platform for data scientists that is built on IBM
added value components only.
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