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A data scientist is evaluating a trained binary classification model. The model has high accuracy but the precision is low and recall is high. Which three actions are most appropriate to improve precision? (Choose three.)
Collecting more training data for the minority class (Option A) helps improve precision because it provides the model with more representative examples of the positive class, reducing the likelihood of false positives. In binary classification, low precision indicates many false …Read full explanation
A large e-commerce company uses a recommendation engine trained on millions of user interactions. Recently, the marketing team noticed a sharp increase in click-through rates for a particular product category. Upon investigation, an engineer found that a competitor had injected fake user profiles that consistently clicked on their products, skewing the training data. The company needs to remediate the attack and prevent future occurrences. The team has limited time and budget. Which course of action should the company take first?
The immediate priority is to remove the poisoned data from the training set and retrain the model, as the fake profiles are actively skewing predictions and causing incorrect click-through rate spikes. This direct remediation addresses the root cause with minimal time and budget,…Read full explanation
Which TWO of the following are key characteristics of unsupervised learning?
Unsupervised learning algorithms, such as k-means clustering or hierarchical clustering, operate exclusively on input data that has no labeled responses. The model must infer the underlying structure directly from the features without any ground-truth outputs to guide it, which i…Read full explanation
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