Data Mining Introductory And Advanced Topics Pdf Free Download PATCHED ⏭
Data Mining Introductory And Advanced Topics Pdf Free Download
next we will look at clustering techniques used for data visualization. the most commonly used clustering technique for visualization is the k-means algorithm. we will also look at two other clustering techniques, one by henderson and nash (1992) and the other by neuhaus et al. (2001). in the last part of the book we will look at some data mining applications. we will start with a couple of applications related to medical diagnosis. we will look at a technique to detect breast cancer using data mining techniques. we will also examine a technique used to detect genotoxic chemicals. next we will look at a technique used to predict the price of a stock. finally we will look at an example of using data mining to detect malicious hacking.
the appendix covers several topics of interest in data mining. in the first part of the appendix we will look at some topics related to data mining. one of the first topics in this part of the appendix is pattern matching.
the data mining algorithms are grouped into different types. these include clustering, classification, association, regression, and novelty detection algorithms. clustering algorithms find patterns or data structures that group together similar data objects. classification algorithms classify unknown data into predefined groups. association algorithms look for patterns and relationships between data objects that are independent of the value of the data. regression algorithms predict the value of an attribute of a data object based on the value of other attributes. novelty detection algorithms find patterns or data structures that are outside the data set used for training.
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