Data Warehousing and Data Mining207810 marksNumerical: DBSCAN clusteringDensity based
How do you compare two classifiers? Given the points A(3,7), B(4,6), C(5,5), D(6,4), E(7,3), F(6,2), G(7,2) and H(8,4), find the core points, border points and outliers using DBSCAN. Take Eps 2.5 and MinPts = 3.
How do you compare two classifiers? Given the points A(3,7), B(4,6), C(5,5), D(6,4), E(7,3), F(6,2), G(7,2) and H(8,4), find the core points, border points and outliers using DBSCAN. Take Eps 2.5 and MinPts = 3.[10]
Two classifiers can be compared using the following techniques: 1. Confusion Matrix based metrics Build a confusion matrix (TP, TN, FP, FN) for each classifier and compute: - Accuracy $= \dfrac{TP+TN}{TP+TN+FP+FN}$ - Precision $= \dfrac{TP}{TP+FP}$ - Recall $= \dfrac{TP}{TP+FN}$ - F1-score