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Sas calculator12/8/2023 ![]() So, with the training data set created, I’ll open a new machine learning project in SAS Viya Model Studio, selecting my data set from where the algorithm will learn, assign the target variable, add linear regression node, a test node, and click “Run pipeline”. a, b, c, d, …, n are the parameters the machine learning process determines to create the model. ![]() X 1, X 2, X 3, …, X n are the input variables – for the calculator, there only will be X 1 and X 2 as operands.y is the result of the model execution – the result of the addition operation.Linear regression is a simple machine learning algorithm based in the following formula: ![]() The algorithm / model I chose for my compute engine is the linear regression. The image below displays the general setup: I created a training data set in Excel with 100 registers, each of them with two random numbers between 0 and 1 and then the sum of them. I want my model to learn the addition of two numbers. The diagram below represents the process:Ī machine learning model is built from a data set where it self-learns what to do. Next, we’ll apply some extra logic which will perform subtraction, multiplication, and division. We’ll perform the addition by normal means of adding two numbers. We start with the addition operation and build from there. Create a machine learning model as the compute-engine Step 4 - Publish the artifact created as an API service (web app created outside of this post) Step 1. Step 3 - Step 3 - Embed the needed logic into the decision to perform the calculator operations (Intelligent Decisioning) Step 2 - Determine how to process other mathematical operations Step 1 - Create a machine learning model representing the compute-engine of my calculator (Model Studio) The steps that I am identifying to complete my challenge are:
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