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Regression analysis is common, usually where there is a relationship with a dependent variable and an independent variable.

This example uses multiple linear regression analysis with fertilizer and rainfall to predict yield (of crops)

I’ve already read in the .CSV file of data, and selected Multiple Linear Regression as the algorithm.

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I will also save the model and give it a name.

I execute the regression model

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The regression results can be reviewed with Visual Intelligence (see last column for Predicted Values)

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In the results area you can look at the algorithm as shown above.

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Using Visual Intelligence you can see a close relationship with the predicted values and the yield in the line graph.

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So now we will feed in project data and reuse the saved model of algorithm.

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The screen shot above shows the rows 8-13 with the blank yield – these are the records we will use to project the predicted values.

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Above shows the predicted results of the yield in rows 8-13

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