Suppose a company has hourly readings from 800 sensors for a whole year that are used to monitor theworkings of a large system of industrial equipment. Given some labeled anomalies, an engineer wants to build a classifier to predict anomalies from future readings of these sensors. She trains a machinelearning model and uses 10-fold cross-validation to tune hyper-parameters (using vanilla methods from scikit-learn, for example). When new data comes in, however, the accuracy of the classifier is poor. She is confused as the cross-validation error was quite good. What might explain these results?

Analyzing operational changes operating results for department b of delta company during 2016 are as follows: sales $540,000 cost of goods sold 378,000 gross profit 162,000 direct expenses 120,000 common expenses 66,000 total expenses 186,000 net loss $(24,000) suppose that department b could increase physical volume of product sold by 10% if it spent an additional $18,000 on advertising while leaving selling prices unchanged. what effect would this have on the department's net income or net loss? (ignore income tax in your calculations.) use a negative sign to indicate a net loss answer; otherwise do not use negative signs with your answers. sales $answer cost of goods sold answer gross profit answer direct expenses answer common expenses answer total expenses answer net income (loss) $answer