data miningdatabasessamplingdata reductionscaling‐upalgorithmsmodel validationChristian H. WeiUniversity of Würzburg Institute of Mathematics Department of Statistics Würzburg GermanyAmerican Cancer SocietyWeiß, C.H.: Sampling in data mining. In: Ruggeri, F., et al. (eds.) Ency- clopedia of ...
In data mining, data sampling serves four purposes: 1. It can reduce the number of data cases submitted to the modeling algorithm. In many cases, you can build a relatively predictive model on 10%–20% of the data cases. After that level, the addition of more cases has sharply diminishin...
1 Introduction Industrial databases often contain millions of tuples but most data mining al- gorithms suffer from limited applicability to only small sets of examples. In principle, two main alternatives exist. First, scaling up data mining algorithms makes their applications to larger data sets ...
Data mining is a complex process that aims to derive an accurate pre-dictive model starting from a collection of data. Traditional approaches assume that data are given in advance and their quality, size and structure are independent parameters. In this paper we argue that an extended vision of...
In data mining or the process of Knowledge Discovery in Databases, interesting patterns and knowledge are discov- ered from large amounts of data. A pattern is interesting if it is valid on test data with some degree of certainty, novel, useful, and easy to understand [5]. Data mi...
Poor sampling (or no sampling) results in bad data that will very likely have a negative impact on outcomes associated with decisions based on that data, both in short-term operation and in longer-term financial impacts. This is why McLanahan takes the time to understand your process and ...
As discussed in the last section, data acquisition in a digital oscilloscope is accomplished by digital sampling and data storage. To capture enough details of the waveform, the sampling has to be continuous at a fast enough rate compared to the time scale of the waveform. This is referred to...
Datamininginlargedatasetsoftenrequiresasamplingor summarizationsteptoformanin-corerepresentationofthe datathatcanbeprocessedmoreefficiently.Uniformrandom samplingisfrequentlyusedinpracticeandalsofrequently criticizedbecauseitwillmisssmallclusters.Manynatural phenomenaareknowntofollowZipf’sdistributionandthe inabilityofun...
With the rapid expansion of data, the problem of data imbalance has become increasingly prominent in the fields of medical treatment, finance, network, etc. And it is typically solved using the oversampling method. However, most existing oversampling met
As early as 1922 Rudolfs reported that carbon dioxide was an attractant for mosquitoes, and that carbon dioxide produced by breathing was an important factor in attracting mosquitoes to their hosts. Since then there have been differences of opinion as to