ARM 401 - Chapter 4 UPDATED ACTUAL Questions and CORRECT
Answers
1. Economic data Data regarding interest rates, asset prices, exchange rates, the Consumer Price
Index, and other information about the global, the national, or a regional economy
2. Predictive model A model used to predict an unknown outcome by means of a defined target
variable.
3. Target variable The predefined attribute whose value is being predicted in a data analytical model.
4. Overfitting The process of fitting a model too closely to the training data for the model to be
effective on other data.
5. Accuracy In model performance evaluation, a model's correct predictions divided by its total
predictions
6. Precision In model performance evaluation, a model's correct positive predictions divided by
its total positive predictions.
7. Recall In model performance evaluation, a model's correct positive predictions divided by
the sum of its correct positive predictions and incorrect negative predictions.
8. Classification A supervised learning technique that uses a structure similar to a tree to segment
Tree data according to known attributes to determine the value of a categorical target
variable.
9. Cluster Analysis A model that determines previously unknown groupings of data.
10. Data Mining The process of extracting hidden patterns from data that is used in a wide range
of applications for research and fraud detection
11. Centrality Mea- In a social network context, the quantification of a node's relationship to other
sure nodes in the same network.
12. Big Data Sets of data that are too large to be gathered and analyzed by traditional methods.
Answers
1. Economic data Data regarding interest rates, asset prices, exchange rates, the Consumer Price
Index, and other information about the global, the national, or a regional economy
2. Predictive model A model used to predict an unknown outcome by means of a defined target
variable.
3. Target variable The predefined attribute whose value is being predicted in a data analytical model.
4. Overfitting The process of fitting a model too closely to the training data for the model to be
effective on other data.
5. Accuracy In model performance evaluation, a model's correct predictions divided by its total
predictions
6. Precision In model performance evaluation, a model's correct positive predictions divided by
its total positive predictions.
7. Recall In model performance evaluation, a model's correct positive predictions divided by
the sum of its correct positive predictions and incorrect negative predictions.
8. Classification A supervised learning technique that uses a structure similar to a tree to segment
Tree data according to known attributes to determine the value of a categorical target
variable.
9. Cluster Analysis A model that determines previously unknown groupings of data.
10. Data Mining The process of extracting hidden patterns from data that is used in a wide range
of applications for research and fraud detection
11. Centrality Mea- In a social network context, the quantification of a node's relationship to other
sure nodes in the same network.
12. Big Data Sets of data that are too large to be gathered and analyzed by traditional methods.
