Step 5: Compare performance of the models

Using the R² values, we create a plot to compare the Minitab model and the Python model.

#Plots
import matplotlib.pyplot as plt 
import seaborn as sns
ax = sns.regplot(x=pyPred,y=predictionsFromModelOps)
ax.set(xlabel='MLP Model Predictions', ylabel='MSS Model Predictions',title="Prediction Comparison between MSS and MLP Models")

R2List = {"MLP $R^2$":[R2Value_Python],
          "MSS $R^2$":[R2Value_MSS]}
R2Table = pandas.DataFrame.from_dict(R2List)
R2Table

	MLP R2	MSS R2
0	0.847415	0.862006

Let's also compare the MAD values.

MADList = {"MLP Mean Absolute Deviation":[MADValue_Python],
          "MSS Mean Absolute Deviation":[MADValue_MSS]}
MADTable = pandas.DataFrame.from_dict(MADList)
MADTable

	MLP Mean Absolute Deviation	MSS Mean Absolute Deviation
0	20131.055468	18561.12182