Question

can someone do instruction 1.7 for me?

In [852]: YOU ARE REQUIRED TO INSERT YOUR CODES IN THIS CELL X_for_10_LR - X[1, np.where(np.array([feature_names_X])[] - 'Situps)[0]] Y_for_10_LR - V1, np.where(np.array([label_names_Y])[0 - 'Waist')[0]] # first, compute the number of samples in the training set: n_train - int(len(Y_for_10_LR)* 8.7) • The training set is the first n_train samples in the dataset X_train - X_for_10_LR[: n_train] Y_train - Y_for_10_LRC: _train) + The test set is the remaining samples in the dataset X_train,x_test,Y_train,y_test. train_test_split(xy, test_size = 0.3, shuffle - True, randon_state - 123 ) x_test - X_for_10_LRE: n_test] Y_test - Y_for_10_URL_test] # Print the number of samples in the training set print('The number of samples in the training set:) print(len(X_train) print(len(Y_train)) Print the number of samples in the test set print('The number of samples in the test seti) println(x_test)) print(lency_test)) The number of samples in the training set: 14 14 The number of samples in the test seti

Answer 1

Working code implemented in Python and appropriate comments provided for better understanding:

Source code for Instruction 1.7:

# YOU ARE REQUIRED TO INSERT YOUR CODES IN THIS CELL
# Construct a plot, where you will show the regression line for Waist vs Situps, the training data (use blue colour),
# the testing data (use green colour), and the residuals for the testing data.
plt.scatter(X_train, Y_train, color='blue')
plt.scatter(X_test, Y_test,color='green')
plt.plot(X_test, Y_pred, color='green', linewidth=2)

Code and Output Screenshots:

Instruction 1.7 Construct a plot, where you will show the regression line for Waist vs Situps, the training data (use blue colour), the testing data (use green colour), and the residuals for the testing data. [Total marks: 5] In [0]: # YOU ARE REQUIRED TO INSERT YOUR CODES IN THIS CELL # Construct a plot, where you will show the regression line for Waist vs Situps, the training data (use bl ue colour), # the testing data (use green colour), and the residuals for the testing data. plt.scatter(X_train, Y_train, color='blue') plt.scatter(X_test, Y_test, color='green') plt.plot(X_test, Y_pred, color='green', linewidth=2) Out[@]: [<matplotlib.lines.Line 2D at 0x7f88d0a47390>] 46 44 42 40 38 36 34 32 50 75 100 125 150 175 200 225 250

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