Three classification models were trained on a dataset of pre…
Three classification models were trained on a dataset of previous bank transactions with the goal of detecting fraudulent transactions. The first model (M1), which is complex, has a training error of 0.0034. The second model (M2), which is simpler, has a training error of 0.0047. The third model (M3), which is the simplest, has a training error of 0.1251. Which model would be the best one to use for classifying future transactions?
Read DetailsYou want to train a model for detecting stones that contain…
You want to train a model for detecting stones that contain gold. A mining company has a dataset of 5 million stone images, of which only 500 contain gold. What is the best measure to evaluate your model if you designate stone images with gold as the positive class?
Read DetailsYou are given a dataset of cars and asked to train a decisio…
You are given a dataset of cars and asked to train a decision tree to classify the cars into two classes: Luxury and Sports. If a leaf node contains 100 cars, which case would provide better performance? (L represents the Luxury class, and S represents the Sports class.)
Read DetailsYou want to train a model for detecting bald eagles. Nationa…
You want to train a model for detecting bald eagles. National Geography provides you a dataset of 1 million bird images, of which only 200 are bald eagles. What is the best measure to evaluate your model if you designate bald eagles as the positive class?
Read DetailsYou are given a dataset of agricultural products and asked t…
You are given a dataset of agricultural products and asked to train a decision tree to classify the products into two classes: Fruits and Vegetables. If a leaf node contains 100 products, which case would provide better performance? (F represents the Fruits class, and V represents the Vegetables class.)
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