add link to video 7
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@ -46,7 +46,7 @@ This repo contains IPython notebooks from my scikit-learn video series, as seen
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- What are some evaluation metrics for regression problems?
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- How do I choose which features to include in my model?
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7. Cross-validation for parameter tuning, model selection, and feature selection (video, [notebook](http://nbviewer.ipython.org/github/justmarkham/scikit-learn-videos/blob/master/07_cross_validation.ipynb), blog post)
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7. Cross-validation for parameter tuning, model selection, and feature selection ([video](https://www.youtube.com/watch?v=6dbrR-WymjI&list=PL5-da3qGB5ICeMbQuqbbCOQWcS6OYBr5A&index=7), [notebook](http://nbviewer.ipython.org/github/justmarkham/scikit-learn-videos/blob/master/07_cross_validation.ipynb), blog post)
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- What is the drawback of using the train/test split procedure for model evaluation?
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- How does K-fold cross-validation overcome this limitation?
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- How can cross-validation be used for selecting tuning parameters, choosing between models, and selecting features?
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