c5- CA CE The figure below shows training data with two features, with each example labeled as being in the positive (filled-in points) or negative (open points) class. Proposed linear discriminant functions (Cl through C6) are shown as dotted lines, each one indicating a different classifier for this data. Each classifier classifies points to the upper-right of its dotted line as positive and points to the lower-left of its dotted line as negative. (a) Draw the coverage plot for this data and plot the different classifiers (and label them as Ci, C2, etc.). (b) Draw the ROC plot and label the classifiers on the plot. (C) Which classifiers have the highest and lowest accuracy? (d) Which classifiers have the highest and lowest precision? (e) Which classifiers have the highest and lowest recall? (1) Which classifiers (if any) are complete? (g) Which classifiers (if any) are consistent? c5- CA CE The figure below shows training data with two features, with each example labeled as being in the positive (filled-in points) or negative (open points) class. Proposed linear discriminant functions (Cl through C6) are shown as dotted lines, each one indicating a different classifier for this data. Each classifier classifies points to the upper-right of its dotted line as positive and points to the lower-left of its dotted line as negative. (a) Draw the coverage plot for this data and plot the different classifiers (and label them as Ci, C2, etc.). (b) Draw the ROC plot and label the classifiers on the plot. (C) Which classifiers have the highest and lowest accuracy? (d) Which classifiers have the highest and lowest precision? (e) Which classifiers have the highest and lowest recall? (1) Which classifiers (if any) are complete? (g) Which classifiers (if any) are consistent