Initialization

Initialization strategies provide the initial labelings from which the first classifier is created. They are merely intended for experimental purposes and therefore some of them may require knowledge about the true labels.

Initialization Strategies

• random_initialization()

• random_initialization_stratified()

• random_initialization_balanced()

Functions

small_text.initialization.strategies.random_initialization(x, n_samples=10)

Randomly draws from the given dataset x.

Parameters

• x – A supported dataset.

• n_samples (int) – Number of samples to draw.

Returns

indices – Numpy array containing indices relative to x.

Return type

np.array[int]

small_text.initialization.strategies.random_initialization_stratified(y, n_samples=10)

small_text.initialization.strategies.random_initialization_balanced(y, n_samples=10)