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#How to use clementine player how to#
#How to use clementine player update#

With powerful sequencing and prediction algorithms, Clementine contains the necessary tools to discover exactly what guests do at a Web site and deliver exactly the products or information they desire.Clementine has successfully helped businesses attract and retain the most valuable customers in a variety of industries. Customer relationship management can be improved thanks to smart classification of customer types and accurate predictions of churn.Governments around the world use data mining to explore massive data stores, improve citizen relationships, detect occurences of fraud such as money laundering and tax evasion, detect crime and terrorist patterns, and enhance the expanding realm of e-goverment.Following is a sample of the types of problems data mining can help solve. A hands-on demonstration of building streams, deriving fields, using graphs, and modeling in Clementine.Ī wide variety of organisations use Clementine to help them mine vast repositories of data.An overview of the types of data-mining problems Clementine can help solve.You can explore your data, fitting different models and investigating different relationships, until you find useful information. In contrast to more traditional statistical methods, you do not necessarily need to know what you are looking for when you start. This view is useful when taking inventory of data, streams, models, etc.Īs a data mining application, Clementine offers a strategic approach to finding useful relationships in large data sets. The Classes tab provides a way to organize your work in Clementine categorically-by the types of objects you create.

For both experienced and first-time data miners, using the CRISP-DM tool will help you to better organize and communicate your efforts. The CRISP-DM tab provides a way to organize projects according to the Cross-Industry Standard Process for Data Mining, an industry-proven, nonproprietary methodology.

There are two ways to view projects you create in Clementine-Classes view and CRISP-DM view.

On the bottom right side of the window is the projects tool, used to create and manage data mining projects. Note: The Models tab replaces the Generated Models tab from earlier versions of Clementine. Models can be examined closely, added to the stream, exported, or annotated. The Models tab is a powerful tool that contains all generated models (models that have been built in Clementine) for a session. You can display, rename, and close the tables, graphs, and reports listed here The Outputs tab contains a variety of files produced by stream operations in Clementine. You can save and close streams as well as add them to a project. The Streams tab contains all streams open in the current session. These tabs are used to view and manage a variety of Clementine objects. On the top right side of the window are the output and object managers. You can jump ahead now using the Contents button below.

You will learn more about building streams later in this tutorial. You then connect them to create a stream, representing the flow of data.

To add nodes to the canvas, double-click icons from the node palettes or drag and drop them onto the canvas.

Most of the data and modeling tools in Clementine reside in palettes, the area below the stream canvas.Įach tab contains groups of nodes that are a graphical representation of data mining tasks, such as accessing and filtering data, creating graphs, and building models. This is the main area you will use to work in Clementine.

The tools here are used to help you create a visual representation of data mining operations.įirst, the area in the middle is called the stream canvas.

When you first start Clementine, the workspace opens in the default view. Working in Clementine is essentially like using a visual metaphor to describe the world of data, statistics, and complex algorithms.Īlthough it may take a minute to shift into this paradigm, you will soon find that Clementine's simplicity-of-use is exceedingly powerful.

Each process in Clementine is represented by an icon, or node, that you connect to form a stream representing the flow of data through a variety of processes.

All of the files shown in the examples are installed with Clementine so that you can follow along.Ĭlementine uses a visual approach to data mining that provides a tangible way to work with data.

The second part is a step-by-step guide to data mining in Clementine.

#How to use clementine player update#

The first part provides a tour of the workspace, including an update of what's new in this version of Clementine.

#How to use clementine player how to#

This tutorial will introduce you to the Clementine toolkit for data mining and show you how to get started with your own data mining project.