8-1數(shù)據(jù)倉庫與數(shù)據(jù)挖掘-預(yù)覽頁
【正文】 ) is too expensive ? Usually OK to have slightly outofdate data at warehouse ? Data/updates are periodically downloaded form online transaction processing (OLTP) systems. ? What schema to use ? Schema integration 169。Silberschatz, Korth and Sudarshan Database System Concepts 6th Edition Decision Support Systems ? Decisionsupport systems are used to make business decisions, often based on data collected by online transactionprocessing systems. ? Examples of business decisions: ? What items to stock? ? What insurance premium to change? ? To whom to send advertisements? ? Examples of data used for making decisions ? Retail sales transaction details ? Customer profiles (ine, age, gender, etc.) 169。Silberschatz, Korth and Sudarshan Database System Concepts 6th Edition Chapter 20: Data Analysis ? Decision Support Systems ? Data Warehousing ? Data Mining ? Classification ? Association Rules ? Clustering 169。Silberschatz, Korth and Sudarshan Database System Concepts 6th Edition Data Warehousing 169。Silberschatz, Korth and Sudarshan Database System Concepts 6th Edition Data Warehouse Schema 169。Silberschatz, Korth and Sudarshan Database System Concepts 6th Edition Decision Tree 169。Silberschatz, Korth and Sudarshan Database System Concepts 6th Edition Best Splits (Cont.) ? Measure of “cost” of a split: Informationcontent (S, {S1, S2, ….., Sr})) = – ? ? Informationgain ratio = Informationgain (S, {S1, S2, ……, Sr}) Informationcontent (S, {S1, S2, ….., Sr}) ? The best split is the one that gives the maximum information gain ratio log2 r i 1 |Si| |S| |Si| |S| 169。 for each attribute A evaluate splits on attribute A。Silberschatz, Korth and Sudarshan Database System Concepts 6th Edition Na239。Silberschatz, Korth and Sudarshan Database System Concepts 6th Edition Association Rules ? Retail shops are often interested in associations between different items that people buy. ? Someone who buys bread is quite likely also to buy milk ? A person who bought the book Database System Concepts is quite likely also to buy the book Operating System Concepts. ? Associations information can be used in several ways. ? ., when a customer buys a particular book, an online shop may suggest associated books. ? Association rules: bread ? milk DBConcepts, OSConcepts ? Networks ? Left hand side: antecedent, right hand side: consequent ? An association rule must have an associated population。ve algorithm 1. Consider all possible sets of relevant items. 2. For each set find its support (., count how many transactions purchase all items in the set). ? Large itemsets: sets with sufficiently high support 3. Use large itemsets to generate association rules. 1. From itemset A generate the rule A {b } ?b for each b ? A. ? Support of rule = support (A). ? Confidence of rule = support (A ) / support (A {b }) 169。Silberschatz, Korth and Sudarshan Database System Concepts 6th Edition Hierarchical Clustering ? Example from biological classification ? (the word classification here does not mean a prediction mechanism) chordata mammalia reptilia leopards humans snakes crocodiles ? Other examples: Inter directory systems (., Yahoo, more on this later) ? Agglomerative clustering algorithms ? Build small clusters, then cluster small clusters into bigger clusters, and so on ? Divisive clustering algorithms ? Start with all items in a single cluster, repeatedly refine (break) clusters into smaller ones 169。Silberschatz, Korth and Sudarshan Database System Concepts 6th Edition Figure 169。Silberschatz, Korth and Sudarshan Database System Concepts 6th Edition 演講完畢，謝謝觀看！
數(shù)學(xué)相關(guān)推薦
鄂ICP備17016276號-1