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Conversely, if the market price tags or pierces the lower band, it means that the market is oversold (ie, there has been too much selling) Once again, just because the price touches the lower band and remains there doesn t mean it will suddenly reverse It can remain oversold for a long time If you observe Bollinger Bands long enough, you ll also notice that the market will linger along the upper or lower bands for a while Many people get impatient when the market walks the bands Unfortunately, that is a misconception The market could stay there indefinitely before turning around and heading toward the center That being said, often that s exactly what happens The market will touch the upper or lower band and immediately reverse and head toward the center Some people might ask: Who cares if the market is overbought or oversold I m glad you asked! First of all, remember that in the default settings, Bollinger Bands are set for two standard deviations above the 20-day moving average As you remember from a previous discussion, for the market to pierce the upper or lower bands, it must make a very strong move After all, two standard deviations are well outside the norm In other words, it is a warning sign A market won t usually remain in that condition for too long before changing direction To answer the question above, although there are no guarantees, when you see that the market is overbought or oversold, it s time to pay attention If other indicators corroborate what you see, then it could be time to take action

set myFile to alias "Macintosh HD:Users:guy:Documents:User Guidepdf" tell my_mess tell the content make new attachment with properties {file name:myFile} at after last paragraph end tell end tell

If you maintain a website, you might be interested in usage patterns. Credit card issuers would like to find fraudulent transactions. Advanced email spam filters use data mining. And much, much more, depending on your imagination!

The Cross-Industry Standard Process for Data Mining (CRISP-DM) defines four main distinct steps of a data mining project. The steps, also shown in figure 1, are as follows: Identifying the business problem Using DM techniques to transform the data into actionable information Acting on the information Measuring the result In the first step, you need to contact business subject matter experts in order to identify business problems. The second step is where you use SQL Server BI suite to prepare the data and train the models on the data. This chapter is focused on the transform step. Acting means using patterns and rules learned in production. You can use data mining models as UDM dimensions; you can use them for advanced SSIS transformations; you can use them in your applications to implement constraints and warnings; you can create RS reports based on mining models and predictions; and more. After deployment in production, you have to measure improvements of your business. You can use UDM cubes with mining model dimensions as a useful measurement tool. As you can see from figure 1, the project doesn t have to finish here: you can continue it or open a new project with identifying new business problems. The second step, the transform step, has its own internal cycle. You need to understand your data; you need to make an overview. Then you have to prepare the data for data mining. Then you train your models. If your models don t give you desired results, you have to return to the data overview phase and learn more about your data, or to the data preparation phase and prepare the data differently.

Resonant circuits often consist of coils and capacitors in series or parallel, but there are other kinds of hardware that exhibit resonance Some of these are as follows

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