Ultimate Step by Step Guide to Machine Learning Using Python: Predictive modelling concepts explained in simple terms for beginners by Anis Daneyal
Author:Anis, Daneyal [Anis, Daneyal]
Language: eng
Format: epub
Published: 2020-02-15T16:00:00+00:00
In the above code sample, we used the train_test_split function in the Scikit-learn library. As you can see, we defined ‘y’ as the target / dependent variable ‘SalePrice’ and ‘X’ as all the independent variables that will be used to predict the price.
We will take a moment here to describe the purpose of the additional parameters in the train_test_split function:
1) test_size – defines what percentage of your data will be treated as test dataset. For this example, we used 50%
2) random_state – is used as an input into random number generation during the split. For our example, we used 80
3) shuffle – is used to determine whether data should be shuffled before splitting. For our purpose, we set that to true
Now we are ready to build, train and test the predictive models!
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Computer Vision & Pattern Recognition | Expert Systems |
Intelligence & Semantics | Machine Theory |
Natural Language Processing | Neural Networks |
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