help ASAP What output metric are we trying to improve with using Classification methods?Question $325$ pts When we're evaluating a classification model using Cross Validation in RapidMiner, what does the performance $("$per$")$ output look like? A table of results, with the model's overall accuracy A scatterplot of the predictions and the actual results A line chart A root mean squared error $($RMSE$)$Question $225$ pts What is the formula for the overall accuracy of Classification Model?Question $125$ pts When outcomes are binary, predictive methods like k$-$nearest neighbors that are based on the results from similar data points cannot compute average outcomes for those data points. What do they do instead? They make the classification randomly They look only at the single most similar data point They only provide a classification if all of those data points had the same outcome They base the classification on a majority vote among those data points