DTSA 5505 - Data Mining Methods (Study Cards) Exam questions and 100% verified answers| latest updater

DTSA 5505 - Data Mining Methods (Study Cards) Exam questions and 100% verified answers| latest updater market basket analysis an unsupervised data mining technique for determining sales patterns Frequent Pattern Mining closed pattern X = no super-pattern Y given X with the same support; max-pattern X = no super-pattern Y given X Apriori Algorithm A fast method of finding frequent itemsets, which also involves pruning non-frequent items and self-joining of k-itemsets only if their first (k-1) items are the same. What challenges are there with apriori algorithm? multiple scans of whole dataset, huge number of candidates, support counting of all candidates Improvements for apriori algorithm? Partitioning, Sampling, Transaction reduction Vertical data format Mining frequent itemsets using the ________________________ is a method that transposes the rows of a given data set into columns. FP-Growth Algorithm If 'd' is frequent in DB | abc, then abcd is frequent (avoid candidate generation) Association Rules Association rules specify a relation between attributes that appears more frequently than expected if the attributes were independent. Correlation rules Measure of dependent/correlated events: lift(A,B) = P(A U B) / P(A)P(B) Rules of lift (correlation) lift = 1 (independent), lift 1 (positive), lift 1 (negative) Metarule-Guided Mining P1 and P2 and ..... and Px = Q1 and Q2 and .... and Qy Supervised Learning Predefined classes, training data with groundtruth label Unsupervised Learning No predefined classes; aims to identify potential clusters/patterns Classification categorical class labels (e.g. fraud detection) Prediction Continuous numerical values (e.g. stock prices) Steps of Classification 1. Learning (Training Data, class labels, model construction) 2. Classification (test data, model evaluation) What is considered in evaluation criteria?