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Greetings! Welcome to Venky Raos blog on Data Miningand Predictive Analytics. This blog aims to de-mystify predictive analytics for the layman.

My blog is featured on: http://www.kdnuggets.com/ - Analytics and Data Mining Resources AND http://www.datasciencecentral.com/ - The Online

Resource for Big Data Practitioners.

TheMainstreamSeer

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We then add a Type node to identify the measurement type of each of Field and assign Roles to each

field. Note from the image below that all fields here are assigned the role of "Target" since we want to

forecast values for each of these fields. The date field is assigned the role "None":

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The output now appears as follows:

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incorrect format. We then add a filter node to filter out the old date field with the incorrect format as

follows:

We then add another Type node to assign the "None" role to the new date field as follows:

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The Time Intervals node allows you to specify intervals and generate labels for time series data to

be used in a Time Series modeling or a Time Plot node for estimating or forecasting. A full range of

time intervals is supported, from seconds to years. For example, if you have a series with daily

measurements beginning January 3, 2005, you can label records starting on that date, with the

second row being January 4, and so on. You can also specify the periodicityfor example, five days

per week or eight hours per day (IBM SPSS Modeler Help).

The time interval node is used to specified specify intervals as follows:

Before we insert the Time Series modeling node, there is one last action that needs to be taken with

respect to the Time Interval node. This is in the Forecast tab of the Time Intervals node where we tick

the "Extend records into the future" box and choose the number of months for which we want to

create the forecast for:

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We are now ready to insert the Time Series modeling node into the modeling canvas and attach it to

the Time Intervals node. We choose the default options as follows and Run the node:

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Posted by Venky Rao at 5:57 PM

Finally, we attach a Time Plot node to the modeling nugget and evaluate the results:

As can be seen from the above time plot, the model has created a forecast for SKU ID AAAAA

extending the historical sales numbers by the specified 6 months.

http://bluelineplanning.com

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