To analyze, manage and make a decision of such type of huge amount of data there are need to techniques called the data mining which will transforming in many fields. In Data Mining data sets will be explored to yield hidden and unknown predictions which can be used in future for the ...
Classification in data mining involves classifying a set of data instances into predefined classes. Learn more about its types and features with this blog.
Supervised and unsupervised approaches in practice Why is data mining important and where is it used? The volume of data that is being produced each year is phenomenally huge. And, what is an already gargantuan figure is doubling every two years. The digital universe is made up of around 90...
In general terms, Data is often termed as the information that can be the collection of numbers, facts, or any other relevant information. Through data, organizations can take actions that are completely based on the insights collected after analyzing the data. In this article, we will explore ...
Huang, Z.: Extensions to the k-means algorithm for clustering large data sets with categorical values. In: Data Mining and Knowledge Discovery, vol. 2, pp. 283–304 (1998) Google Scholar Plant, C., Böhm, C.: Inconco: interpretable clustering of numerical and categorical objects. In:...
of the techniques and tools available in data mining tool kits. The choice of tool or technique is somewhat automated in that the techniques will be applied according to how the question is posed. In earlier times, data mining was referred to as “slicing and dicing” the database, but ...
This chapter discusses the classification of different types of data sets. A data set consists of some basic measurement or measurements of individual items or things called “elementary units,” which may be people, households, firms, cities, or just about anything of interest. The same piece ...
In the era of information explosion, more and more data piles up. However, these dense data are unfocused and less readable. So we need data visualization to help data to be easily understood and accepted. By contrast, visualization is more intuitive and
Then two event types are similar if their sets of contexts are similar. We quantify this by using a simple approach of computing centroids of sets of contexts and using the L 1 distance. We present empirical results on telecommunications alarm sequences and student enrollment data, showing that...
We will explore the concept of Big Data Analytics, its features, benefits, and methods for deriving valuable insights from vast amounts of unprocessed data.