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Gain superior analytical depth with a suite of statistical, data mining and machine-learning algorithms. Open source integration with R. Perform data transformation and exploration, and train and score supervised and unsupervised models in R. High-performance capabilities. Boost performance with the included high-performance data mining nodes.
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Veri Madenciliğine Giriş. Kadir Alan. ·. Follow. 6 min read. ·. Nov 22, 2017. İnsan sınıflandırmasının yetersiz kaldığı bilginin arttığı bir süreçteyiz. Büyük ölçekli bu veriler arasında bilgiyi ulaşma ve bilgiyi analiz etme, bilgiden anlam çıkarma ve tahmin yürütme bilimine veri madenciliği denir.
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Business users and subject-matter experts with limited statistical skills can generate their own models using SAS Rapid Predictive Modeler. An easy-to-use GUI steps them through a workflow of data mining tasks. Analytics results are displayed in easy-to-understand charts that provide the insights needed for better decision making.
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Aşağıdaki uygulamalardan birini kullanarak madencilik modelleri oluşturabilirsiniz: Intelligent Miner PMML biçiminde madencilik modelleri oluşturur. Madencilik modelleri Db2 içinde depolanır. Diğer araçlar PMML biçiminde madencilik modelleri sağlayan başka bir araç; örneğin, SAS Enterprise Miner (SAS EM) ya da SPSS® Clementine)
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Complete the following steps to add users and groups to the Factory Miner: User role: In SAS Management Console, select the User Manager plug-in. Right-click the Factory Miner: User role and select Properties. On the Members tab, move the desired users and groups from the Available Identities field to the Current Members field.
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SAS Enterprise Miner Server. Please select a target environment: All server tier machines should have a minimum of 4 GB of memory plus 2 GB for each concurrent user. SAS Enterprise Miner requires a Java Runtime Environment (JRE) on the server tier for all operating systems. Please refer to the SAS 9.3 section of the Third-Party Software ...
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Open, extensible design. Extension node for easily adding tools and personalized SAS code. Interactive editor features for training and score code. Integrate text mining for analysis of both structured and unstructured data. Incorporate time series, Web paths and associations rules as additional input variables into the model development process.
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By default, Enterprise Miner creates a local project that uses your user ID as the name (for this example, Phoenix) and a process flow diagram that is named Untitled. When you reopen Enterprise Miner, the last project you were working with is loaded. Tools tab — contains the Enterprise Miner Tools Palette. The Tools Palette
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Note: To view the data source in the Enterprise Miner user interface, you must specify a location for the Enterprise Miner Global Data Set (EMGDS) library. You should assign the EMGDS library in either your server start-up code or in your project start-up code before you run sample code similar to the above.
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Valid values for this macro are YES and NO, and the default value is NO. This variable is available only in SAS Enterprise Miner 7.1 and later. RPM_DEBUG — This macro variable is used by the EM_RPM macro, and controls information sent to the log file. Use this feature only in conjunction with SAS Technical Support.
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Overview of SAS Enterprise Miner. SAS Enterprise Miner is a flexible and powerful data mining package designed to streamline the data mining process. SAS Enterprise Miner creates highly accurate predictive and descriptive models based on vast amounts of data that is gathered by an organization. It offers a rich, easy-to-use set of …
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SAS Enterprise Miner streamlines the data mining process to create highly accurate predictive and descriptive models based on analysis of vast amounts of data from across an enterprise. Data mining is applicable in a variety of industries and provides methodologies for such diverse business problems as fraud detection, ing, …
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When you use SAS Enterprise Miner, you can do it in 2 ways: 1- Using the client installed in your machine. this client will look into the sassw.config file, locally in your SASHOME folder. This filw can reference a local sas-environment.xml or a sas-environment.xml file located directly on your web server (an URL). This client will be able …
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2 5. Select Enterprise Miner, one machine when prompted for a plan in the Plan Deployment window. 6. Select Single Account when prompted to select one account or multiple accounts. 7. Follow the instructions in the Install and Configuration windows. Note: During the SAS 9.1 Foundation installation, be sure to select English with DBCS and …
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SAS Enterprise Miner streamlines the data mining process to create highly accurate predictive and descriptive models based on analysis of vast amounts of data from across an enterprise. Data mining is applicable in a variety of industries and provides methodologies for such diverse business problems as fraud detection, ing, …
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The SAS Enterprise Miner toolbar shortcut buttons are a graphic set of user interface tools that you use to perform common computer functions and frequently used SAS Enterprise Miner operations. The text name of any tool button is displayed when you position your mouse pointer over the button.
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Here are some recommendations for memory on SAS Enterprise Miner 15.2 client and server machines. Client — a minimum of 4 GB of physical RAM dedicated to the SAS Enterprise Miner 15.2 product running on the client machine. Server — a minimum of 6 GB of physical RAM, plus 2 GB per concurrent user. Mid-Tier — a minimum of 8 GB of …
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