What Is The Purpose Of Tools, Like Clementine Data Mining?
Clementine Data Mining is a business process, developed for minimization of the time for resolving problems. Clementine supports the process of data mining, namely access to data, transformations, modelling, evaluation and introduction. By means of Clementine data mining the methodology CRISP-DM is carried out.
The breadth of this technology and thereof the huge variety of the software defines the market of data mining tools. Here is a classification of data mining tools according to Kdnuggets, which are tools of the general and specific purpose. The most popular group of tools contains tooling, classification of data, segmentation, tools of the statistical analysis, Text Mining, Information Retrieval (IR), tools of visualization.
Tooling category consists of universal tools, which include methods of classification and preliminary preparation of data. SPSS is one of the most popular tools and it is supported by the set of data mining methods. SPSS is a statistical package for data processing. SPSS Server 14.0 enables SPSS users to work with greater files of data for acceptance of right decisions.
There are various variants of decisions on introduction of data mining tools. Some of them are: purchase of ready data mining software, purchase of data mining software adapted for a concrete business, development of data mining product for the order from foreign company, development of data mining product by own strength, various combinations of the variants described above, including using of various libraries, components and tool sets for developers, which create built in data mining appendices.
Data mining tools can be estimated by various criteria. The estimation of data mining software from the user's point of view is defined by an estimation of a set of its characteristics. They can be divided on two groups: business and technical characteristics. This division is conditional enough, and some characteristics may simultaneously get in both categories.
The program should support the most widespread formats of data: txt, dbf, xls, csv and others. Additional convenience to the user is created at an opportunity of loading and unloading of the certain part of the imported or exported fields at the choice of the user.
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