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Error Output With Multiple Regression? | Rate this: (3/5 from 2 votes) |
Hi, I'm new to multiple regression I try it out today with some data and the out was SUMMARY OUTPUT Regression Statistics Multiple R 1 R Square 1 Adjusted R Square 65535 Standard Error 0 Observations 3 ANOVA df SS MS F Significance F Regression 11 0.19201459 0.017455872 #NUM! #NUM! | ||
BenWTS | ||
Posted by benwts on |
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Rate this: (2.2/5 from 5 votes) I suggest that download the multiple regression and analysis template from this site here, and you will be able to intepret the results and also forecast with a user friendly interface. | |
Excel Business Forums Administrator | |
Posted by Excel Helper on |
Rate this: (2/5 from 2 votes) so can uyou plz help me out for the following. | |
Posted by jaimin on |
Rate this: (2.5/5 from 2 votes) | |
Excel Business Forums Administrator | |
Posted by Excel Helper on |
Rate this: (4/5 from 2 votes) 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 | |
Posted by RachelGomez161999 on |
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