a sensitivity of 98% and a specificity of 96%. if the prevalence of the disease in the population is 0.1%, what is the probability that a person who tests positive actually has the disease. 3. A machine learning model is designed to pred
1. A machine learning model is trained to predict whether a given image contains a certain object or not. The model has an accuracy of 90% a false positive rate of 5%, and false negative rate of 8%. if 20% of the images in the dataset contain the object, what is the probability that an image identified as containing the object by the model actually contains the object?
2. A diagnostic test for a rare disease has a sensitivity of 98% and a specificity of 96%. if the prevalence of the disease in the population is 0.1%, what is the probability that a person who tests positive actually has the disease.
3. A machine learning model is designed to predict whether a given stock will go up or down in price. the model has an accuracy of 75%, a false positive rate of 20%, and a false negative rate of 15%. if 60% of the stocks in the dataset go up in price, what is the probability that a stock identified as going up in price by the model actually goes up in price?
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