![]() ![]() The goal of classification can be to guess whether a customer will steal money (yes or no) given the values of other attributes (the age, gender city and education) of a customer. ![]() Consider that steal-money? is an attribute that indicate whether a customer has stolen some money or not (yes or no). Each record (customer) may be described using various attributes such as age, gender, city, education and steal-money?. For example, consider data about customers of a bank. The goal of classification is to guess the missing value of an attribute called the target attribute based on the values for the other attributes. The KNN algorithm takes as input a dataset that consists of a set of records, described using attributes, assumed to be nominal attributes (strings). Well-known and described in many artificial intelligence and data KNN is designed for classifying instances (a classifier). The KNN algorithm is a very simple and popular algorithm for classification. This example explains how to run the KNN algorithm using the SPMF open-source data mining library. SPMF documentation >How to train the KNN Classifier to Perform Classification ( SPMF documentation) ![]()
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