[Q48-Q70] 合格させちゃうSAS Institute SAS A00-255試験簡単かつ正確なPDF問題 [2025年05月14日]

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合格させちゃうSAS Institute SAS A00-255試験簡単かつ正確なPDF問題 [2025年05月14日]

A00-255認証試験問題集解答を提供しています

質問 # 48
Impute the missing values for the variable TLSum using the Tree method. What is the mean of the new variable (with the imputed values)?
Response:

  • A. 30,000-39,999.99
  • B. 20,000-29,999.99
  • C. less than 19,999.99
  • D. 40,000 or higher

正解:C


質問 # 49
Which model was picked as the best model by SAS Enterprise Miner?
Response:

  • A. Decision Tree (3-way)
  • B. Regression
  • C. Decision Tree
  • D. None of the above

正解:C


質問 # 50
-> Add a Decision Tree node after the Impute node with TARGET as the dependent variable and all other input variables as independent variables (main effects only).
- Allow for 1 substitute rule in case the variable for the primary splitting rule is missing.
- Disable pruning for the decision tree.
-> Add another Neural Network node after the decision tree with TARGET as the dependent variable and all other input variables as independent variables (main effects only).
- Configure the Neural Network model to use Average Error for Model Selection Criterion.
-> Run the process flow.
What is the number of input variables being used by the Neural Network Model?
Enter your numeric answer in the space below:
Response:

  • A. 0
  • B. 1
  • C. 2
  • D. 3

正解:A


質問 # 51
Perform these tasks in SAS Enterprise Miner:
- Add a Decision Tree node after the Impute node with TARGET as the dependent variable and all other input variables as independent variables (main effects only). Configure the decision tree to use 1 for Number of Surrogate Rules and Largest for Method in Subtree. Do not change any other property of the Decision Tree node.
- Add another Neural Network node after the decision tree with TARGET as the dependent variable and all other input variables as independent variables (main effects only). Configure the Neural Network model to use Average Error for Model Selection Criterion. Do not change any other property for the Neural Network node. Run the process flow.
How many leaves are there in the decision tree?
Response:

  • A. 21 or more
  • B. 16-20
  • C. 11-15
  • D. 1-10

正解:C


質問 # 52
For the variable InqTimeLast, which term best describes the shape of its distribution?
Response:

  • A. bimodal
  • B. right skewed
  • C. left skewed
  • D. symmetric

正解:B


質問 # 53
You are building a model to identify fraud. Your model will produce predictions that can be interpreted as the probability of fraud. You will pass on the top 100 scoring cases to management for investigation. Assume that you have sufficient data to hold out a validation and test data set for model evaluation.
Which selection would represent a reasonable ordering of fit statistics (best to worst) for this situation?
Select one:
Response:

  • A. R-square, AIC, K-S statistic
  • B. ROC index, ASE, misclassification rate
  • C. Misclassification rate, ROC index, ASE
  • D. ASE, Lift for the top 10%, ROC index

正解:B


質問 # 54
Perform these tasks in SAS Enterprise Miner:
- Add a Decision Tree node after the Impute node with TARGET as the dependent variable and all other input variables as independent variables (main effects only). Configure the decision tree to use 1 for Number of Surrogate Rules and Largest for Method in Subtree. Do not change any other property of the Decision Tree node.
- Add another Neural Network node after the decision tree with TARGET as the dependent variable and all other input variables as independent variables (main effects only). Configure the Neural Network model to use Average Error for Model Selection Criterion. Do not change any other property for the Neural Network node. Run the process flow.
In the validation data, the lift corresponding to the fourth decile is in which of the following ranges?
Response:

  • A. 1.75 or more
  • B. 0-1.24999
  • C. 1.25-.49999
  • D. 1.5-1.74999

正解:D


質問 # 55
Perform these tasks in SAS Enterprise Miner:
- Add a Decision Tree node after the Impute node with TARGET as the dependent variable and all other input variables as independent variables (main effects only). Configure the decision tree to use 1 for Number of Surrogate Rules and Largest for Method in Subtree. Do not change any other property of the Decision Tree node.
- Add another Neural Network node after the decision tree with TARGET as the dependent variable and all other input variables as independent variables (main effects only). Configure the Neural Network model to use Average Error for Model Selection Criterion. Do not change any other property for the Neural Network node. Run the process flow.
Which of the following variables was used in the decision tree model?
Response:

  • A. TLDel3060Cnt24
  • B. TLDel90Cnt24
  • C. IMP_TLSatCnt
  • D. InqFinanceCnt24.

正解:A


質問 # 56
Perform these tasks in SAS Enterprise Miner:
* Add a Decision Tree node, as shown below. (Make sure you use only default options in the Decision Tree node.)

* Run the Decision Tree node.
In the training data set, consider only those observations for which the actual value of the target variable equals 1, TARGET=1. What percentage of these observations is being correctly predicted by the decision tree?
Response:

  • A. 14.6216
  • B. 66.6667
  • C. 80.3571
  • D. 0

正解:D


質問 # 57
What is the kurtosis value for the variable TLDel60Cnt24?
Response:

  • A. between 14 and 16.99
  • B. 17 or higher
  • C. less than 10
  • D. between 10 and 13.99

正解:A


質問 # 58
Refer to the exhibit:

The SAS data set retail contains information on the count of retail store sales based on the following item types: bargain, essential, gourmet, and health. Based on the results from the Cluster Profile node, which statement is true?
Select one:
Response:

  • A. The overall distribution of bargain item sales is left-skewed and Segment 4 contains stores selling fewer than average bargain items.
  • B. The overall distribution of essential item sales is approximately normal and Segment 1 contains stores selling fewer than average essential items.
  • C. The overall distribution of essential item sales is right skewed and Segment 4 contains stores selling higher than average essential items.
  • D. The overall distribution of bargain item sales is approximately normal and Segment 1 contains stores selling fewer than average bargain items.

正解:D


質問 # 59
Look over the output from the Neural Network model. Which of the following statement(s) is (are) true?
Response:

  • A. The misclassification error for the test data is 0.154255.
  • B. The optimization for the model has not been completed.
  • C. All of the above
  • D. The model has too few input variables.

正解:B


質問 # 60
Refer to the exhibit:

What would be the decision threshold (probability cutoff) generated for this decision matrix. You may use a calculator for this question. On the certification exam, an on-screen calculator is provided for you.
Select one:
Response:

  • A. 0.18
  • B. 0.27
  • C. 0.82
  • D. 0.21

正解:A


質問 # 61
Which method of input selection for regression analysis evaluates the statistical significance of all included inputs after each input is added?
Select one:
Response:

  • A. Simple
  • B. Stepwise
  • C. Forward
  • D. Backward

正解:B


質問 # 62
Refer to the exhibit:

The SAS data set credit_customers contains a numeric variable units_sold that holds only the values: 1, 2, 3, 4. Based on the settings provided in the Advanced Advisor Options, what will be the Role and Level of the units_sold variable when the credit_customers data set is created using Advanced Metadata Advisor in the Data Source Wizard?
Select one:
Response:

  • A. Role: InputLevel: Nominal
  • B. Role: IntervalLevel: Input
  • C. Role: InputLevel: Interval
  • D. Role: RejectedLevel: Nominal

正解:A


質問 # 63
What is the variable worth of the PromCntCardAll variable in Segment 1?
Select one:
Response:

  • A. 0.10844
  • B. 0.27649
  • C. 0.24169
  • D. 0.24914

正解:B


質問 # 64
Sometimes in predictive modeling we build models using a sample that has a primary outcome proportion different from true population proportion. This is usually done when the ratio of primary to secondary outcomes in a binary target variable in the population is close to which of the following?
Response:

  • A. 0
  • B. 0.05
  • C. 1.2
  • D. 0.8

正解:B


質問 # 65
Perform these tasks in SAS Enterprise Miner:
* Add a Decision Tree node, as shown below. (Make sure you use only default options in the Decision Tree node.)

* Run the Decision Tree node.
What percentage of all observations is being correctly predicted in the test data set by the decision tree?
Response:

  • A. 83.1126%
  • B. 85.2222%
  • C. 16.8874%
  • D. 84.5212%

正解:A


質問 # 66
In segment 2, what percentage of GiftAvgCard36 values are between 6.6638 and 11.998?
Select one:
Response:

  • A. 48.59%
  • B. 14.00%
  • C. 47.82%
  • D. 13.39%

正解:A


質問 # 67
Assume that a company has an excellent customer segmentation in place and the segment scheme is a variable in the input data set. What is the best partition method that one should use?
Select one:
Response:

  • A. Stratify
  • B. Systemic
  • C. Random
  • D. Cluster

正解:A


質問 # 68
Assume a variable is coded as follows: 1=unmarried, 2=married, 3=divorced, and 4=widowed. Then which of the following measurement levels should be selected in SAS Enterprise Miner for this variable?
Response:

  • A. Nominal
  • B. Ordinal
  • C. Unary
  • D. Interval

正解:A


質問 # 69
Which of the following is not true about results produced by the Regression node?
Response:

  • A. Model Information provides you with information that includes the number of target categories and the number of model parameters.
  • B. Variable Summary information identifies the roles of variables used by the Regression node.
  • C. Type 3 Analysis of Effects provides you with information about the number of parameters that each input contributes to the model.
  • D. Fit Statistics can provide information that affects decision predictions, but does not affect estimate predictions.

正解:D


質問 # 70
......


SASInstitute A00-255試験に合格することは、SAS Enterprise Minerを使用した予測モデリングの分野での専門知識を示す素晴らしい方法です。この認定は、業界の他の専門家との差別化を図ることができ、新しい求人機会を見つける際に競争力を与えることができます。さらに、SASの認定を取得することで、データアナリストまたはデータサイエンティストとしての信頼性を高め、収益性を向上させることができます。キャリアの見通しを向上させたい場合や、SAS Enterprise Minerを使用した予測モデリングの知識を深めたい場合は、A00-255試験は優れた選択肢です。

 

検証済みで更新されたA00-255問題集と解答で100%一発合格保証の問題集:https://drive.google.com/open?id=1-Na-bQzW31OVuObjl-vWoLKDav7A_DF8

更新されたA00-255試験練習テスト問題:https://www.passtest.jp/SASInstitute/A00-255-shiken.html