CODEWITHSUNDEEP
pythonscikit-learnmnist
afettouhi
afettouhi

Reputation: 75

Visualizing Manifold Learning MNIST digit data fails

I am doing some exercises with MNIST digits data but it fails when I try to visualize it. The exercise is from a book BTW. So I import the the dataset

from sklearn.datasets import fetch_openml
mnist = fetch_openml('mnist_784')
mnist.data.shape

then I just plot part of the data

fig, ax = plt.subplots(6, 8, subplot_kw=dict(xticks=[], yticks=[]))
for i, axi in enumerate(ax.flat):
    axi.imshow(mnist.data[1250 * i].reshape(28, 28), cmap='gray_r')

then I perform my analysis on 1/30th of the data

# use only 1/30 of the data: full dataset takes a long time!
data = mnist.data[::30]
target = mnist.target[::30]

model = Isomap(n_components=2)
proj = model.fit_transform(data)
plt.scatter(proj[:, 0], proj[:, 1], c=target.astype(int), 
            cmap=plt.cm.get_cmap('jet', 10)) # need to convert target into int
plt.colorbar(ticks=range(10))
plt.clim(-0.5, 9.5);

I am only interested in the 1 from the dataset and I want to see those and this were I get the error. Here is what I run

from sklearn.manifold import Isomap

# Choose 1/4 of the "1" digits to project
data = mnist.data[mnist.target == 1][::4]

fig, ax = plt.subplots(figsize=(10, 10))
model = Isomap(n_neighbors=5, n_components=2, eigen_solver='dense')
plot_components(data, model, images=data.reshape((-1, 28, 28)),
                ax=ax, thumb_frac=0.05, cmap='gray_r')

this results in a 

ValueError: Found array with 0 sample(s) (shape=(0, 784)) while a minimum of 1 is required.

I don't understand why the array is empty?

Upvotes: 2

Views: 264

Answers (1)

Mohsin hasan
Mohsin hasan

Reputation: 837

Target values for mnist data are strings and not integers.

Just change this line:

data = mnist.data[mnist.target == 1][::4]

to:

data = mnist.data[mnist.target == '1'][::4]

Upvotes: 3

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