# Generate the dataset
num_instances = 10000
num_features = 784
X = np.random.rand(num_instances, num_features)

# Instantiate and train a PCA object
pca = PCA()
pca.fit(X)

# Compute the explained variance ratio
eva = pca.explained_variance_ratio_

print(np.round(eva, decimals=4)