Chapter 2 error during prediction about handson-ml HOT 2 CLOSED

thanks @ageron , makes sense

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Hi @singh-krishan ,

Thanks for your question. Make sure you fit estimators only on training data. This means you should call fit() or fit_transform() or fit_predict() only on training data, never on other data (such as the validation set, the test set, or new data). In your code, you should therefore replace full_pipeline.fit_transform(some_data) with full_pipeline.transform(some_data). However, before you do that, you should first fit the model on the training set.
So the code should look like:

housing_prepared = full_pipeline.fit_transform(housing)
some_data_prepared = full_pipeline.transform(some_data)

In the full training set, there are 5 distinct values in the ocean_proximity column. That's why after the full_pipeline is fit on the training set, it outputs one-hot vectors of size 5 for each ocean_proximity category. But if some_data is small enough, it is likely to contain less categories, which is what you observed. But if you only call transform(some_data) and not fit_transform(some_data), it will output one-hot vectors of size 5.

Hope this helps.

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