From the course: Machine Learning and AI Foundations: Value Estimations
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Retrain the classifier with fresh data
From the course: Machine Learning and AI Foundations: Value Estimations
Retrain the classifier with fresh data
- [Instructor] We finished building and using a working machine learning model. Congratulations! But remember, our machine learning model is only as accurate as the data we trained it with. Since house prices are always changing, the model will quickly get out of date as the market changes. So when the underlying data changes, we need to retrain the model. We can retrain our model using the same trainmodel.py file we used earlier. We just need to provide an updated dataset with more recent home sales data. Let's take a look. First, here's the accuracy results we got when we trained the estimator with the original dataset. The test set error is around $59,000. Let's see what happens when we retrain the model with an updated dataset. First, I'm going to right-click on the output and choose Pin Tab. This will keep these results visible so that we can compare them later. Now, let's change the dataset we are using. We just need to update the name of the data file we are loading. I provided…
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