Answers for "Machine Learning and JMX data"
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The latest answers for the question "Machine Learning and JMX data"Answer by skoelpin
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So lets back up and discuss the math behind how this will predict.. Remember the old equation y=mx+b?
We will apply that here, where the Y represents the field you want to predict where x is going to represent your predictor field (dependent variable). Lets talk simple linear regression with 1 dependent variable
First off, forget the `predict` command and lets do this in the MLTK. You will first need to fit your model and select a dependent variable which has a relationship with your independent variable. You can establish this relationship by fitting your model and reading the output, RMSE and line of best fit graphs. If there's little to no relationship then the dots will not hug that line of best fit and the RMSE will measure how far the residual points were from the expected field. You will need to use this feedback to determine if your field is a good field to help predict your independent variable. You also need to have a good sample size your model is looking over and I typically like to have an 80/20 split between learning and testing.Thu, 15 Mar 2018 15:03:07 GMTskoelpin