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Corrected and added some stuff #7

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Merged
merged 3 commits into from
May 9, 2015
Merged

Corrected and added some stuff #7

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b4b8d15
corrected mistake with n1 and added code to embed in slidify
elmerehbi May 8, 2015
0648694
added phrase about ROC curves
elmerehbi May 8, 2015
41691f1
removed a line left by mistake
elmerehbi May 8, 2015
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added phrase about ROC curves
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@elmerehbi
elmerehbi committed May 8, 2015
commit 06486942d71d359f76a00073767028d6540c1bf7
1 change: 1 addition & 0 deletions 8_PREDMACHLEARN/Practical Machine Learning Course Notes HTML.Rmd
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Expand Up @@ -213,6 +213,7 @@ grid.raster(readPNG("figures/6.png"))


## Receiver Operating Characteristic Curves
* are commonly used techniques to measure the quality of a prediction algorithm.
* predictions for binary classification often are quantitative (i.e. probability, scale of 1 to 10)
- different cutoffs/threshold of classification (> 0.8 --> one outcome) yield different results/predictions
- **Receiver Operating Characteristic** curves are generated to compare the different outcomes
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1 change: 1 addition & 0 deletions 8_PREDMACHLEARN/Practical Machine Learning Course Notes.Rmd
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Expand Up @@ -214,6 +214,7 @@ grid.raster(readPNG("figures/6.png"))
$\pagebreak$

## Receiver Operating Characteristic Curves
* are commonly used techniques to measure the quality of a prediction algorithm.
* predictions for binary classification often are quantitative (i.e. probability, scale of 1 to 10)
- different cutoffs/threshold of classification (> 0.8 --> one outcome) yield different results/predictions
- **Receiver Operating Characteristic** curves are generated to compare the different outcomes
Expand Down