new StochasticNetwork()
Network that samples training data
into mini batches, in order to learn
more quickly with less processing
without sacrificing significant accuracy.
- Implements:
- Source:
Methods
train(training_data, options) → {array}
Given training data, a number of epochs, and a learning rate,
trains the network to more accurately predict
correct outputs for given inputs.
The second parameter accepts an object containing custom training settings, specifically:
epochs: number of rounds to train against the data. Defaults to 20,000.
learning_rate: value between 0 and 1 representing how quickly the network learns. Defaults to 0.3.
threshold: error threshold. if the network attains an error rate under this threshold, it stops training early. Defaults to 0.005.
Parameters:
| Name | Type | Description |
|---|---|---|
training_data |
array | array of [input, correct_output] pairs used to train the network |
options |
object | options object. |
- Implements:
- Source:
Returns:
[i, error] where i is the number of iterations it took to reach the returned error rate
- Type
- array