ISYE 6501 - Finals sample Quiz Prep 2025

GT ISYE 6501



ISYE 6501 - Finals sample Quiz Prep
2025
Select the type of problem that Linear Regression is best suited for.


- Classification
- Clustering
- Experimental design
- Prediction from feature data
- Prediction from time-series data

- Variable selection -Correct Answer ✔- Prediction from feature data


Useful when you want to model the relationship between a dependent variable and
one or more independent variables with a linear assumption.


Select the type of problem that ARIMA is best suited for.


- Classification and/or prediction from feature data
- Clustering
- Experimental design
- Prediction from time-series data

- Variable selection -Correct Answer ✔- Prediction from Time-series data


Useful when you want to forecast future values in a time series (e.g., stock prices,
sales) and have historical time-ordered data available.

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Select the type of problem that logistic regression is best suited for.


- Classification and/or prediction from feature data
- Clustering
- Experimental design
- Prediction from time-series data

- Variable selection -Correct Answer ✔- Classification and/or prediction from
feature data


Useful when you want to model the probability of a binary outcome (0 or 1) based
on one or more predictor variables.


Select the type of problem that lasso regression is best suited for.


- Classification and/or prediction from feature data
- Clustering
- Experimental design
- Prediction from time-series data

- Variable selection and/or prediction from feature data -Correct Answer ✔-
Variable Selection and/or prediction from feature data


Useful when you want to perform variable selection and regularization in linear
regression models, reducing the impact of irrelevant features.




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,GT ISYE 6501


Select the type of problem that support vector machine is best suited for.


- Classification and/or prediction from feature data
- Clustering
- Experimental design
- Prediction from time-series data

- Variable selection -Correct Answer ✔- Classification and/or prediction from
feature data


Useful when you want to classify data into different categories and have labeled
training data.


Select the type of problem that k-means is best suited for.


- Classification and/or prediction from feature data
- Clustering
- Experimental design
- Prediction from time-series data
- Prediction from feature data

- Variable selection -Correct Answer ✔- Clustering


Useful when you want to cluster data into k distinct groups based on similarity and
have unlabeled data.


Select the type of problem that GARCH is best suited for.


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, GT ISYE 6501




- Classification and/or prediction from feature data
- Clustering
- Experimental design
- Prediction from time-series data
- Prediction from feature data

- Variable selection -Correct Answer ✔- Prediction from Time-series data


Useful when you want to model and forecast the volatility of financial time series
data (e.g., stock returns) and have data with time-varying variance.


Select the type of problem that exponential smoothing is best suited for.


- Classification and/or prediction from feature data
- Clustering
- Experimental design
- Prediction from time-series data
- Prediction from feature data

- Variable selection -Correct Answer ✔- Prediction from time-series data


Useful when you want to generate short-term forecasts based on weighted averages
of past observations and have time series data with trends or seasonality.


Select the type of analysis that ARIMA is best suited for.



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