Data Science Qustion Refrence:…
Question Answered step-by-step Data Science Qustion Refrence:… Data Science QustionRefrence: https://github.com/ShmilyJxu/Shared/blob/main/20220501%20(2).ipynbSetup Code:# We’ll import that tools you’ll need.# You may import additional tools if you wish to.import numpy as npfrom sklearn.tree import DecisionTreeClassifierfrom sklearn.ensemble import RandomForestClassifierfrom sklearn.model_selection import train_test_splitfrom sklearn import datasetsimport matplotlib.pyplot as plt%matplotlib inlinePlot the feature importanceAdd code to the cell below and run it, to help you answer the following question.Working with the trained Model 3, get the feature importance values from the model, and reshape them into an 8×8 array (matrix), so they are ordered like one of the 8×8 digit images (see code below to clarify). Then plot the importance matrix as an image.Q11: Which best describes the pattern exhibited by the matrix of feature importances?a. Pixels near the edges of the images are most important.b. Pixels near the edges of the images are least important.c. All pixels are nearly equally important. There is little variation#################### Part 3 of 3#################### Reshape the pixels of a sample into an 8×8 matrix, and plot.digit_sample = X[0,:] # get single image sampledigit_matrix = np.reshape(digit_sample, (8, 8)) # reshape from 64 pixel vector to 8×8 pixel matrixplt.figure()plt.imshow(digit_matrix)plt.colorbar()### Add to (edit) the code below to create the importance matrix as instructed above.
