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Questions and Answers
What is the appropriate method to fill in the NaN’s present in a column with categorical variables?
What is the appropriate method to fill in the NaN’s present in a column with categorical variables?
- Mean
- Median
- Mode (correct)
- None of the above
What is the probability of failure of an air conditioning system due to a gas leak?
What is the probability of failure of an air conditioning system due to a gas leak?
- 55/72
- 87/104
- 87/107
- 55/107 (correct)
Given evidence of a gas leak in the failure of an air-conditioning system, what is the probability that electrical failure could have occurred?
Given evidence of a gas leak in the failure of an air-conditioning system, what is the probability that electrical failure could have occurred?
- 55/87
- 72/107
- 55/72 (correct)
- 55/107
Given evidence of electrical failure in an air-conditioning system, what is the probability that a gas leak could also have occurred?
Given evidence of electrical failure in an air-conditioning system, what is the probability that a gas leak could also have occurred?
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Which metric is used for the continuous output problem?
Which metric is used for the continuous output problem?
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Study Notes
Dealing with NaN's in Categorical Variables
- For categorical variables, it's not suitable to fill NaN's with mean or median values, as it may not make sense in the context of the data.
- Instead, possible approaches include:
- Removing rows with NaN values
- Replacing NaN values with a new category (e.g., "Unknown")
- Using a model that can handle missing values (e.g., decision trees)
Probabilities in Air Conditioning System Failure
- The probability of an air conditioning system failure due to a gas leak is unknown.
- Given evidence of a gas leak, the probability of electrical failure occurring is unknown.
- Given evidence of electrical failure, the probability of a gas leak also occurring is unknown.
Metrics for Continuous Output Problems
- For continuous output problems, a suitable metric is needed to evaluate the model's performance.
- Possible metrics include Mean Squared Error (MSE), Mean Absolute Error (MAE), and R-Squared.
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