Which of the following issues would likely be the most severe in terms of blocking the development of a classification model?Group of answer choicesYour laptop is low on RAM while your data size is large.Half of the features in your data set have low to no predictive value.The label column in your data set has only NULL values.The population sampled has a bias towards older customers
Question
Which of the following issues would likely be the most severe in terms of blocking the development of a classification model?Group of answer choicesYour laptop is low on RAM while your data size is large.Half of the features in your data set have low to no predictive value.The label column in your data set has only NULL values.The population sampled has a bias towards older customers
Solution
The most severe issue in terms of blocking the development of a classification model would be "The label column in your data set has only NULL values."
Here's why:
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"Your laptop is low on RAM while your data size is large." - This is a hardware issue and can be resolved by using more powerful hardware or cloud-based solutions. It might slow down the process but doesn't block the development of a model.
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"Half of the features in your data set have low to no predictive value." - This is not ideal but it doesn't block the development of a model. These features can be identified and removed during the feature selection process.
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"The label column in your data set has only NULL values." - This is a critical issue. In a classification problem, the label column is what we want to predict. If all the values are NULL, we have nothing to learn from and thus, cannot develop a model.
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"The population sampled has a bias towards older customers" - This might affect the accuracy of the model if it's not representative of the entire population, but it doesn't block the development of a model. It's a problem of sample bias, which can be addressed by collecting more diverse data.
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