A00-255問題集でリアル試験問題でテストエンジン問題集でトレーニング
SASInstitute A00-255テスト問題集とオンライン試験エンジン
SASInstitute A00-255 認定試験は、SAS Enterprise Miner 14 を使用した SAS 予測モデリングの専門知識を証明するために受験するのが挑戦的でありながら報酬がある試験です。適切な準備と勉強をすれば、求職者は試験に合格し、データ分析のキャリアを進めるための貴重な資格を取得することができます。
SASInstitute A00-255認定試験は、データの準備、変数の選択、モデルの選択、モデルの評価、および展開など、さまざまなトピックをカバーしています。候補者は、SAS Enterprise Miner 14を使用してモデリングのためのデータを準備し、適切な変数を選択し、様々な技術を使用して予測モデルを構築し、モデルのパフォーマンスを評価し、プロダクション環境でモデルを展開する能力がテストされます。また、基本的な統計的概念とSASプログラミングの理解を示すことが求められます。
質問 # 26
Refer to the following profit matrix and confusion matrix for a campaign soliciting product purchases. The predicted variable is a binary outcome.
Based on the above tables, what is the average profit? 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
- B. 6.9
- C. 86.25
- D. 1
正解：A
質問 # 27
In SAS Enterprise Miner's Decision Tree node, which of the following types of target variable can be used?
Response:
- A. all of the above
- B. binary
- C. nominal with any number of categories
- D. interval
正解：A
質問 # 28
The selected model, based on the misclassification rate for the validation data, has how many input variables?
Response:
- A. 4 or more
- B. 0
- C. 1
- D. 2
正解：D
質問 # 29
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.
Now suppose that the bank expects to make a profit of $200 USD when TARGET=1, but it expects to lose $25 USD when TARGET=0. Incorporate the above scenario, change the assessment measure of the decision tree to average square error, and then run the Decision Tree node. What is the total profit for the test data set?
Response:
- A. 1,000-1,599
- B. 1,600 or higher
- C. less than or equal to 299
- D. 300-999
正解：B
質問 # 30
If we were to add a Transformation node, what would be the default transformation for interval inputs for the present scenario?
Response:
- A. Maximum Normal
- B. Optimal
- C. none of the above
- D. Maximum Correlation
正解：C
質問 # 31
Perform this task using SAS Enterprise Miner:
Continue to use the same diagram. Use an Ensemble node (configure using default options) in SAS Enterprise Miner to combine all four models.
Compare the performance of the ensemble and the four models using average squared error in the validation data. Which is the best model in this comparison?
Response:
- A. Decision Tree
- B. Ensemble
- C. Neural Network
- D. Regression
正解：B
質問 # 32
What is the kurtosis value for the variable TLDel60Cnt24?
Response:
- A. 17 or higher
- B. between 14 and 16.99
- C. less than 10
- D. between 10 and 13.99
正解：B
質問 # 33
Look over the output from the Neural Network model. Which of the following statement(s) is (are) true?
Response:
- A. The model has too few input variables.
- B. The optimization for the model has not been completed.
- C. All of the above
- D. The misclassification error for the test data is 0.154255.
正解：B
質問 # 34
Open the diagram labeled Practice A within the project labeled Practice A. Perform the following in SAS Enterprise Miner:
1. Set the Clustering method to Average.
2. Run the Cluster node.
What is the Cubic Clustering Criterion statistic for this clustering?
Response:
- A. 5.00
- B. 5862.76
- C. 67409.93
- D. 14.69
正解：D
質問 # 35
Perform these tasks in SAS Enterprise Miner:
- Use the Regression node to build another regression model with TARGET as the dependent variable and all other input variables as independent variables (main effects only).
- Configure the regression model to use Stepwise for Selection Model and Validation Error for Selection Criteri a. Do not change any other property for the regression model.
For the validation data, in what range does cumulative percent captured response at the 60th percentile lie?
Response:
- A. 25-49.99
- B. 75 or more
- C. 0-24.99
- D. 50-74.99
正解：B
質問 # 36
If you only consider observations for which TARGET=0, what percentage of such observations has BanruptcyInd=1?
Response:
- A. 80% or higher
- B. between 50%-79.99%
- C. less than 15%
- D. between 15%-49.99%
正解：C
質問 # 37
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 decision tree model, what is the importance of the variable InqCnt06?
Response:
- A. 0.15-0.299999
- B. less than 0.149999
- C. 0.45 or higher
- D. 0.30-0.449999
正解：D
質問 # 38
Perform these tasks in SAS Enterprise Miner:
- Use the Regression node to build another regression model with TARGET as the dependent variable and all other input variables as independent variables (main effects only).
- Configure the regression model to use Stepwise for Selection Model and Validation Error for Selection Criteri a. Do not change any other property for the regression model.
Consider the variable TLCnt03 in the selected model. Based on the model results, changing this variable by 1 unit will result in which of the following?
Response:
- A. reduction of odds for TARGET=1 by 0.708
- B. change of odds for TARGET=1 by a factor 0.708
- C. change of odds for TARGET=1 by a factor 0.3457
- D. reduction of odds for TARGET=1 by 0.3457
正解：B
質問 # 39
1. Create a project named Insurance, with a diagram named Explore.
2. Create the data source, DEVELOP, in SAS Enterprise Miner. DEVELOP is in the directory c:\workshop\Practice.
3. Set the role of all variables to Input, with the exception of the Target variable, Ins (1= has insurance, 0= does not have insurance).
4. Set the measurement level for the Target variable, Ins, to Binary.
5. Ensure that Branch and Res are the only variables with the measurement level of Nominal.
6. All other variables should be set to Interval or Binary.
7. Make sure that the default sampling method is random and that the seed is 12345.
What is the mean credit card balance (CCBal) of the customers with a variable annuity?
Response:
- A. $11,142.45
- B. $8,711.65
- C. $9,586.55
- D. $0.00
正解：C
質問 # 40
Perform this task using SAS Enterprise Miner:
Continue to use the same diagram. Use an Ensemble node (configure using default options) in SAS Enterprise Miner to combine all four models.
The percentage of observations correctly predicted in the validation data by the Ensemble model is in which of the following ranges?
Response:
- A. 84-89.99%
- B. 94% or higher
- C. 90-93.99%-
- D. less than 83.99%
正解：D
質問 # 41
Perform these tasks in SAS Enterprise Miner:
*Continue to use the same diagram. Define and create the data set CREDIT_SCORE for scoring. The variables (their roles and measurement levels) in the CREDIT_SCORE data should be set as identical to those in the CREDIT dat a. The only exception is that the scoring data does not have a TARGET variable.
* Find the best model out of Decision Tree, Decision Tree (3-way), Regression, and Neural Network as defined by each of the four model's overall performance in the validation data measured by average squared error. Now, use this best model to score the CREDIT_SCORE data.
CREDIT SCORE:
The percentage of TARGET=1 as predicted by the best model on the scoring data is in which of the following ranges?
Response:
- A. 5%-5.99%
- B. under 4.99%
- C. 6%-6.99%
- D. 7% or higher
正解：B
質問 # 42
An analyst is performing a market basket analysis (affinity analysis) on the purchase of Shaving Cream and Seltzer Water. The purchase data from a set of 250 customers is shown below:
What is the confidence of the rule "Shaving Cream implies Seltzer Water"? You may use a calculator for this question. On the certification exam, an on-screen calculator is provided for you.
Select one:
Response:
- A. 67%
- B. 57%
- C. 40%
- D. 60%
正解：B
質問 # 43
How many hidden layers are generally needed in an MLP-based neural network to capture a discontinuous relationship between inputs and target?
Response:
- A. one hidden layer
- B. no hidden layer, direct connection between inputs and output is preferred
- C. two hidden layers
- D. three or more hidden layers
正解：C
質問 # 44
A useful concept in logistic regression is the doubling amount. How would you calculate doubling amount for an input variable that has a parameter estimate of b1?
Response:
- A. 2*log(b1)
- B. 0.69/b1
- C. 2/log(b1)
- D. 2*b1
正解：B
質問 # 45
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. Forward
- C. Stepwise
- D. Backward
正解：C
質問 # 46
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