What is the likelihood value? Why do prediction models attempt to maximize it? Question content area bottom Part 1 A. The likelihood value allows data scientists to identify misclassified predictions. The higher the likelihood value, the easier it is for the scientists to identify those errors. B. The likelihood value identifies whether the feature variables used to make predictions above the target variable make economic sense. The higher the likelihood variable, the more economic benefit to the business of making the prediction. C. The likelihood value is a measure of the model's ability to give accurate predictions. Models with high likelihood values give better predictions. D. The likelihood value is a measure of the model's rate of failure. Most prediction models aim to minimize the likelihood value rather than to maximize it