Data Science How do you find line of best fit for a 3d model in Python? I have a dataframe with columns x, y, and z. The values create a polynomial scatterplot. I used polynomialfeatures and fit to transform the data. I also did linear regression on the values per teachers instructions. I am not sure if it is correct since there are three axes instead of planar. When I try to make z-test data from x-test and y-test, I can't get the code to work. I am not sure what I am doing wrong. I really need some direction. # Plot Curve Fit x_test = np.linspace(-21,21,1000) y_test = x_test z_test= model.predict(x_test.reshape(-1,1))
Data Science How do you find line of best fit for a 3d model in Python? I have a dataframe with columns x, y, and z. The values create a polynomial scatterplot. I used polynomialfeatures and fit to transform the data. I also did linear regression on the values per teachers instructions. I am not sure if it is correct since there are three axes instead of planar. When I try to make z-test data from x-test and y-test, I can't get the code to work. I am not sure what I am doing wrong. I really need some direction. # Plot Curve Fit x_test = np.linspace(-21,21,1000) y_test = x_test z_test= model.predict(x_test.reshape(-1,1))
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Data Science
How do you find line of best fit for a 3d model in Python?
I have a dataframe with columns x, y, and z. The values create a polynomial scatterplot.
I used polynomialfeatures and fit to transform the data.
I also did linear regression on the values per teachers instructions.
I am not sure if it is correct since there are three axes instead of planar.
When I try to make z-test data from x-test and y-test, I can't get the code to work. I am not sure what I am doing wrong. I really need some direction.
# Plot Curve Fit
x_test = np.linspace(-21,21,1000)
y_test = x_test
z_test= model.predict(x_test.reshape(-1,1))
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