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forecasting:meeting_minutes_september_30_2020 [2020/09/30 22:21] kmacloves |
forecasting:meeting_minutes_september_30_2020 [2021/09/19 21:59] (current) |
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=====Updates===== | =====Updates===== | ||
- | * Completed all regression models | + | * Reviewed regression models and created templates for each model from scratch |
- | * Topics learned: SVR, Decision Tree Regression (DTR), Random Forest Regression (RFR) | + | * Topics learned: Linear Reg, Polynomial Reg, SVR, Decision Tree Reg, Random Forest Reg, |
=====Problems===== | =====Problems===== | ||
* COVID-19 forced today's lab hours to be online | * COVID-19 forced today's lab hours to be online | ||
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* R-squared is the metric used to determine whether or not the regression model fits the data well. | * R-squared is the metric used to determine whether or not the regression model fits the data well. | ||
* A good regression model has an R-squared value close to 1. | * A good regression model has an R-squared value close to 1. | ||
- | * Not one regression model is best. One must evaluate the pros and cons of each regression model in relation to the data when deciding which one to use | + | * Not one regression model is best. One must evaluate the pros and cons of each regression model in relation to the data when deciding which one to use. |