house-price-prediction's People
house-price-prediction's Issues
Find more information from categorical features
It seems we only considered using one-hot encoding to deal with those categorical features.
Is it possible to assign some values to those features?
For example:
For "HeatingQC", apparently, houses with "excellent" heating system have much higher prices. Can we assign "Ex" to, let's say, 50, "Gd" to 40, "TA" to 30, so on and so forth.
And then use those newly assigned values combining with all other data to do regression?
Will it make any improvement?
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