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Supported data models (conceptual, logical, physical) Supported notations Forward engineering Reverse engineering Model/database comparison and synchronization Teamwork/repository Database Workbench: Conceptual, logical, physical IE (Crow’s foot) Yes Yes Update database and/or update model No Enterprise Architect
An example of data mining related to an integrated-circuit (IC) production line is described in the paper "Mining IC Test Data to Optimize VLSI Testing." [12] In this paper, the application of data mining and decision analysis to the problem of die-level functional testing is described. Experiments mentioned demonstrate the ability to apply a ...
The rule that covers the most positive examples and the least negative examples are chosen as the best rule of the current seed example. It allows the best rule to cover some negative examples to handle the increase flexibility and reduce the overfitting problem and noisy data in the rule induction.
Tanagra works similarly to current data mining tools. The user can design visually a data mining process in a diagram. Each node is a statistical or machine learning technique, the connection between two nodes represents the data transfer. But unlike the majority of tools which are based on the workflow paradigm, Tanagra is very simplified.
This kind of analysis is supposedly an example of the use of data mining. A widely used example of cross selling on the web with market basket analysis is Amazon.com's use of "customers who bought book A also bought book B", e.g. "People who read History of Portugal were also interested in Naval History".
Comparison of computer algebra systems; Comparison of deep learning software; Comparison of numerical-analysis software; Comparison of survey software; Comparison of Gaussian process software; List of scientific journals in statistics; List of statistical packages
KNIME (/ n aɪ m / ⓘ), the Konstanz Information Miner, [2] is a free and open-source data analytics, reporting and integration platform.KNIME integrates various components for machine learning and data mining through its modular data pipelining "Building Blocks of Analytics" concept.
icCube reporting and all XMLA compliant visualization tools like Excel, etc Yes Yes Jedox OLAP Server: Yes Yes Yes Cube Rules, SVS Triggers Yes No Yes Microsoft Excel, Qlik, Tableau, Jedox Web, Power BI No Yes Kyvos: Yes Yes Yes No Yes Yes No