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forecasting:meeting_minutes_september_21_2020 [2020/09/21 21:57] kmacloves [Reminders] |
forecasting:meeting_minutes_september_21_2020 [2021/09/19 21:59] (current) |
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| =====Updates===== | =====Updates===== | ||
| - | + | * Started section 9 of the course: Support Vector Regression (SVR). | |
| + | * Topics learned: SVR and Support Vector Machines. | ||
| =====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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| =====Reminders===== | =====Reminders===== | ||
| - | * Support Vector Regression (SVR) uses a //hyper plane// to stratify data and features | + | * Support Vector Regression (SVR) uses a //hyper plane// to stratify data and features. |
| - | * The //best fit// line, created with a simple regression model, paired with the data points (known as the support vectors) assist in creating the bounds of the //hyper plane// | + | * The hyper plane is created with a regression model and is paired with the data points (known as the support vectors) which create a margin. |
| - | * Points within the //hyper plane// are ignored | + | * Points within the margins are ignored because (similar to noise) we want to select data that accurately represents the features. |