BaşlayınÜcretsiz Başlayın

NMF learns the parts of images

Now use what you've learned about NMF to decompose the digits dataset. You are again given the digit images as a 2D array samples. This time, you are also provided with a function show_as_image() that displays the image encoded by any 1D array:

def show_as_image(sample):
    bitmap = sample.reshape((13, 8))
    plt.figure()
    plt.imshow(bitmap, cmap='gray', interpolation='nearest')
    plt.colorbar()
    plt.show()

After you are done, take a moment to look through the plots and notice how NMF has expressed the digit as a sum of the components!

Bu egzersiz

Unsupervised Learning in Python

kursunun bir parçasıdır
Kursu Görüntüle

Egzersiz talimatları

  • Import NMF from sklearn.decomposition.
  • Create an NMF instance called model with 7 components. (7 is the number of cells in an LED display).
  • Apply the .fit_transform() method of model to samples. Assign the result to features.
  • To each component of the model (accessed via model.components_), apply the show_as_image() function to that component inside the loop.
  • Assign the row 0 of features to digit_features.
  • Print digit_features.

Uygulamalı interaktif egzersiz

Bu örnek kodu tamamlayarak bu egzersizi bitirin.

# Import NMF
____

# Create an NMF model: model
model = ____

# Apply fit_transform to samples: features
features = ____

# Call show_as_image on each component
for component in model.components_:
    ____

# Select the 0th row of features: digit_features
digit_features = ____

# Print digit_features
print(digit_features)
Kodu Düzenle ve Çalıştır