Notes

1. Field of the Invention
The present invention relates to data mining and particularly to a novel method of clustering a set of points that includes recovering a set of clusters from a sparsely represented set of points.
2. Description of the Related Art
Data mining refers to a set of techniques that allow a user to analyze data (tables) in order to discover previously unseen patterns of interest. Typically, the data is organized in a rectangular table (also known as a data matrix). Data mining techniques form a table of data (i.e., a data matrix) in a format that allows for ready access and processing by a host of analytical tools. Data mining techniques are typically made possible because a researcher seeks to discover a pattern that is observed in the data, as opposed to looking for a single value or term that is observed in the data. For example, if a researcher seeks to find a pattern that indicates whether a participant exhibited a certain pattern of behavior when taking a particular medication, it may not be immediately apparent what all the participants ate during the course of the study. Rather, the researcher might be more interested in finding a broader pattern in the data that includes eating a certain food at certain times, and not necessarily eating a particular food at a particular time. Thus, it is possible to apply a data mining technique to the data and discover that, for example, a certain food was consumed more frequently at certain times of day, and less frequently at other times of day.
https://best-forex-brokers-ng.com/ Data mining methods typically involve the use of descriptive statistics to summarize the data and preliminary data exploration techniques (e.g., sequential partitioning, cluster analysis) to discover unanticipated patterns. To facilitate the production of useful discoveries from data, a variety of data mining models, techniques, and tools have been developed. Data mining is a useful technology for uncovering complex data patterns. Data mining allows a user to reduce data volumes to a set of items of interest, and then “eavesdrop” on how these items are related to one another. Data mining is a technique that allows a user to discover associations (or patterns) within a set of data. Data mining is therefore a useful tool to discover patterns that are not readily apparent without the application of a data mining methodology.
A variety of different data mining models and models can be utilized to uncover patterns in the data, depending on the context within which the data is being mined. The most basic data mining model is known as a xe2x80x9cSingle Attribute Match
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