無料でゲット！最新の2025年最新の有効な練習SAS Institute SAS A00-255問題と解答でテストエンジン
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SASInstitute A00-255試験は、SAS Enterprise Miner 14を使用した予測モデリングの熟練度をテストするために設計されています。この認定は、データアナリスト、データサイエンティスト、および定期的にデータを扱う他の専門家を対象としています。この試験では、データの準備、変数の選択、回帰分析、決定木、クラスタリング技術など、幅広いトピックがカバーされます。
Sasinstitute A00-255認定試験に登場するには、候補者はSASプログラミングの基本、統計モデリングの概念、およびデータマイニング技術を強く理解する必要があります。この試験では、データ探索、データ変換、可変選択、モデル比較、モデルの展開など、さまざまなトピックに焦点を当てています。また、候補者は、データを効果的に分析およびモデル化するために、SAS Enterprise Minerソフトウェアとの協力の経験も必要です。 Sasinstitute A00-255認定試験に合格すると、候補者がSASエンタープライズマイナーを予測モデリングとデータ分析に効果的に使用するために必要なスキルと知識を持っていることが示されています。
質問 # 21
The importance of an input variable in predicting a target in an MLP-based neural network can be figured out by which of the following?
Response:
- A. none of the above
- B. the highest absolute value of the parameter estimate between the input and any of the hidden neurons multiplied by the absolute value of the parameter estimate of the hidden neuron
- C. the average of the absolute values of parameter estimates between the input and all of the hidden neurons
- D. the highest absolute value of the parameter estimate between the input and any of the hidden neurons
正解：A
質問 # 22
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.
Which of the following variable(s) is (are) statistically significant at the 5% level in the selected model?
Response:
- A. IMP_TLOpen24Pct
- B. TLTimeFirst
- C. all of the above
- D. TLDel3060Cnt24
正解：C
質問 # 23
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. 5862.76
- B. 5.00
- C. 14.69
- D. 67409.93
正解：C
質問 # 24
What is the purpose of the Kass (Bonferroni) adjustment in the decision tree split-search algorithm?
Select one:
Response:
- A. To ensure that the choice of split is not influenced by input measurement scale.
- B. To reduce the number of surrogate splitting rules.
- C. To ensure a non-negative logworth value.
- D. To give categorical inputs a greater chance to be used the split.
正解：A
質問 # 25
Which statement describes the Decision Tree Split Search mechanism for categorical inputs?
Select one:
Response:
- A. All levels are weighted and the weights are used for testing.
- B. A clustering mechanism eliminates observations in outlier clusters as potential split points as a first step. Then, for the remaining observations, the average target value is calculated for each level, and then passed on for testing if it is the optimal split point.
- C. The levels that have target rate of 0 or 100% are re-binned first, then weighted and the weights are used for testing.
- D. The average target value is calculated for each level, and then passed on for testing if it is the optimal split point.
正解：D
質問 # 26
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. 1-10
- B. 16-20
- C. 11-15
- D. 21 or more
正解：C
質問 # 27
For the variable InqTimeLast, which term best describes the shape of its distribution?
Response:
- A. left skewed
- B. bimodal
- C. right skewed
- D. symmetric
正解：C
質問 # 28
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. Interval
- B. Nominal
- C. Ordinal
- D. Unary
正解：B
質問 # 29
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. 1.25-.49999
- B. 1.5-1.74999
- C. 0-1.24999
- D. 1.75 or more
正解：B
質問 # 30
Suppose your input variables have missing values. Before running a decision tree with these input variables, you should do which of the following?
Response:
- A. impute only class variables using the Tree method but do not impute the interval variables
- B. impute all missing values using the Tree method
- C. not impute any missing values because trees can handle them.
- D. impute only interval variables using the Tree method but do not impute the class variables
正解：C
質問 # 31
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 is the probability that TARGET=0 for ID=000355 in the training data?
Response:
- A. 0.9341825902
- B. 0.0658174098
- C. 0.9220647773
- D. 0.077935227
正解：C
質問 # 32
Multicollinearity in regression refers to which of the following?
Response:
- A. non-constant variance of the target variable
- B. high skewness in distributions of input variables
- C. non-normality of the target variable
- D. high correlations among input variables
正解：D
質問 # 33
-> 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 # 34
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. 0.21
- C. 0.27
- D. 0.82
正解：A
質問 # 35
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. 1,600 or higher
- B. 300-999
- C. less than or equal to 299
- D. 1,000-1,599
正解：A
質問 # 36
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.
The variable Branch has how many levels?
Response:
- A. 0
- B. 1
- C. 2
- D. 3
正解：C
質問 # 37
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SASInstituteのA00-255認定試験は、SAS Enterprise Miner 14を使用した予測モデリングの専門知識を示したい専門家にとって有用な資格です。この試験は、データの準備、データ探索、変数選択、モデル技術、モデル評価、展開における候補者の知識とスキルをテストします。認定を取得することは、求人市場での競争力を高め、データ分析分野における卓越への取り組みを示します。
A00-255ブレーン問題集リアル試験最新問題2025年05月03日には87問題：https://www.passtest.jp/SASInstitute/A00-255-shiken.html
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