トップクラスSASInstitute A00-255オンライン問題集で更新された[2025年02月]
A00-255練習問題集で検証済みのJPNTest更新された87問題あります
SASINSTITUTE A00-255（SAS Enterprise Miner 14を使用したSAS予測モデリング）試験は、SAS Enterprise Miner 14を使用して予測モデリングに能力を実証したい専門家向けに設計されています。 、可変選択、データの準備、およびモデル評価。さらに、試験では、SASプログラミング技術と統計分析に関する候補者の知識をテストします。
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。
質問 # 27
Consider a binary target variable. Assume Accuracy is the desired assessment measure. Accuracy is not an option in the Decision Tree node. Which assessment measure can you use as a proxy for accuracy?
Select one:
Response:
- A. Total Profit
- B. 1 - Misclassification Rate
- C. Mean Square Error
- D. Average Squared Error
正解：B
質問 # 28
If we were to add a Transformation node, what would be the default transformation for interval inputs for the present scenario?
Response:
- A. none of the above
- B. Maximum Normal
- C. Optimal
- D. Maximum Correlation
正解：A
質問 # 29
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*b1
- B. 0.69/b1
- C. 2/log(b1)
- D. 2*log(b1)
正解：B
質問 # 30
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: RejectedLevel: Nominal
- C. Role: IntervalLevel: Input
- D. Role: InputLevel: Interval
正解：A
質問 # 31
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 average target value is calculated for each level, and then passed on for testing if it is the optimal split point.
- D. The levels that have target rate of 0 or 100% are re-binned first, then weighted and the weights are used for testing.
正解：C
質問 # 32
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. 1,000-1,599
- C. 300-999
- D. less than or equal to 299
正解：A
質問 # 33
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. less than 83.99%
- C. 90-93.99%-
- D. 94% or higher
正解：B
質問 # 34
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. Random
- B. Stratify
- C. Systemic
- D. Cluster
正解：B
質問 # 35
If you only consider observations for which TARGET=0, what percentage of such observations has BanruptcyInd=1?
Response:
- A. between 15%-49.99%
- B. 80% or higher
- C. less than 15%
- D. between 50%-79.99%
正解：C
質問 # 36
Which model was picked as the best model by SAS Enterprise Miner?
Response:
- A. Decision Tree (3-way)
- B. Decision Tree
- C. None of the above
- D. Regression
正解：B
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 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. 66.6667
- B. 14.6216
- C. 80.3571
- D. 0
正解：D
質問 # 38
The selected model, based on the misclassification rate for the validation data, has how many input variables?
Response:
- A. 0
- B. 1
- C. 2
- D. 4 or more
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.
The variable Branch has how many levels?
Response:
- A. 0
- B. 1
- C. 2
- D. 3
正解：A
質問 # 40
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. 84.5212%
- B. 83.1126%
- C. 85.2222%
- D. 16.8874%
正解：B
質問 # 41
For the variable InqTimeLast, which term best describes the shape of its distribution?
Response:
- A. right skewed
- B. bimodal
- C. left skewed
- D. symmetric
正解：A
質問 # 42
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. three or more hidden layers
- C. no hidden layer, direct connection between inputs and output is preferred
- D. two hidden layers
正解：D
質問 # 43
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. 6%-6.99%
- B. under 4.99%
- C. 5%-5.99%
- D. 7% or higher
正解：B
質問 # 44
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 distribution of the predicted probabilities of TARGET=0 in the scoring data is approximately which of the following?
Response:
- A. left skewed
- B. right skewed
- C. normal
- D. bimodal
正解：A
質問 # 45
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. change of odds for TARGET=1 by a factor 0.708
- B. change of odds for TARGET=1 by a factor 0.3457
- C. reduction of odds for TARGET=1 by 0.708
- D. reduction of odds for TARGET=1 by 0.3457
正解：A
質問 # 46
Multicollinearity in regression refers to which of the following?
Response:
- A. non-normality of the target variable
- B. non-constant variance of the target variable
- C. high correlations among input variables
- D. high skewness in distributions of input variables
正解：C
質問 # 47
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. 50-74.99
- D. 0-24.99
正解：B
質問 # 48
If the bank wanted to select the best model based on the models' overall performances on the validation data as measured by the average squared error, then the best model is which of the following?
Response:
- A. Decision Tree (3-way)
- B. Neural Network
- C. Regression
- D. Decision Tree
正解：C
質問 # 49
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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知識とスキルを実証したい専門家向けに設計されています。この試験は、ヘルスケア、財務、保険、保険などのさまざまな業界のデータを扱う個人を対象としています。とりわけマーケティング。 Sasinstitute A00-255試験の合格は、SAS Enterprise Miner 14を使用して予測モデルを開発し、データパターンを分析し、データの洞察に基づいて情報に基づいた決定を下す候補者の能力を検証します。
最新（2025)SASInstitute A00-255試験問題集：https://www.jpntest.com/shiken/A00-255-mondaishu
更新されたA00-255試験問題集でPDF問題とテストエンジン：https://drive.google.com/open?id=1hR7y83gyx17ghzpWTOLZ0MGD9wLi4_1w