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Error Output With Multiple Regression | Rate this: (4/5 from 2 votes) |
We can define a test problem that we can use to demonstrate the different modeling strategies. We will use the make_regression() function to create a test dataset for multiple-output regression. We will generate 1,000 examples with 10 input features, five of which will be redundant and five that will be informative. The problem will require the prediction of two numeric values. Problem Input: 10 numeric variables.Problem Output: 2 numeric variables.The example below generates the dataset and summarizes the shape. # example of multioutput regression test problemfrom sklearn.datasets import make_regression# create datasetsX, y = make_regression(n_samples=1000, n_features=10, n_informative=5, n_targets=2, random_state=1, noise=0.5)# summarize datasetprint(X.shape, y.shape)Running the example creates the dataset and summarizes the shape of the input and output elements of the dataset for modeling, confirming the chosen configuration. (1000, 10) (1000, 2)Next, let’s look at modeling this problem directly. Regards,Rachel Gomez | ||
rachel | ||
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