Schnick [Support Vector Machine Learning Tool Tester - DE M O]

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This script was written to form part of the article posted on the MQL5 website.
Imagine this hypothetical scenario, you are a researcher investigating a rare animal only found in the depths of the Arctic call Shnicks. Given the remoteness of these animals, only a small handful have ever been found (lets say around 5000). As a researcher, you are stuck with the question... how can I identify a Schnick?

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How can we use this data to identify a new animal as a schnick?
One possible solution to our problem is to use a support vector machine to identify the patterns in the data and create a framework that can be used to classify animals as either a schnick or not a schnick. The first step is to create a set of data that can be used to train your support vector machine to identify schnicks. The training data is a set of inputs and matching outputs for the support vector machine to analyze and extract a pattern from.
This script attempts to demonstrate the power of using support vector machines in solving classification style problems by using the Support Vector Machine Learning Tool available in the . A full description of this hypothetical problem and script can be found in the article . The article includes a walkthrough of how to use the script and how this problem can give insights into using machine learning for assessing market trends.
Code:

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