From the course: Grasshopper: Generative Design for Architecture
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Regression and predictive statistics
From the course: Grasshopper: Generative Design for Architecture
Regression and predictive statistics
- [Instructor] Regression Algorithms may be the most intuitive tool in the machine learning toolbox. They predate machine-learning all together playing a critical role in statistics since the early 1800s. Fundamentally, regression analysis extracts a transfer function from the results of previous test samples. This transfer function then provides a method to predict future output for untested input. There's a wide variety of regression strategies. We will look at some of the options included in lunchbox machine learning tool set for Grasshopper. When picking a regression strategy, typically, you should consider the number and type of inputs and the type of transfer functions to consider. Most importantly linear or nonlinear. I have the exercise file open already. In Grasshopper, you can see there's a data set here. This has been downloaded from a Github repository. The link is included in the script. In the data, we have height, weight, and age and gender for a whole bunch of…
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