Skip to content

Commit eebe6c8

Browse files
fix: TrainStream, CrossValidate, and Typescript
Overhauled the internals of TrainStream and CrossValidate so they are decoupled from the networks themselves, as well as being able to restore or store CrossValidate from json. Added examples for CrossValidate and TrainStream, and as well one for learning math, to test the typescript type file. Too I added missing typescript configs and examples. *
1 parent d9b853e commit eebe6c8

Some content is hidden

Large Commits have some content hidden by default. Use the searchbox below for content that may be hidden.

47 files changed

+17821
-16502
lines changed

README.md

+46-1
Original file line numberDiff line numberDiff line change
@@ -28,6 +28,8 @@
2828
+ [For training with `RNN`, `LSTM` and `GRU`](#for-training-with-rnn-lstm-and-gru)
2929
+ [Training Options](#training-options)
3030
+ [Async Training](#async-training)
31+
+ [Cross Validation](#cross-validation)
32+
+ [Train Stream](#train-stream)
3133
- [Methods](#methods)
3234
+ [train](#train)
3335
- [Failing](#failing)
@@ -274,6 +276,49 @@ With multiple networks you can train in parallel like this:
274276
.catch(handleError);
275277
```
276278

279+
### Cross Validation
280+
[Cross Validation](https://en.wikipedia.org/wiki/Cross-validation_(statistics)) can provide a less fragile way of training on larger data sets. The brain.js api provides Cross Validation in this example:
281+
```js
282+
const crossValidate = new CrossValidate(brain.NeuralNetwork);
283+
const stats = crossValidate.train(data, networkOptions, trainingOptions, k); //note k (or KFolds) is optional
284+
const net = crossValidate.toNetwork();
285+
286+
287+
// optionally later
288+
const json = crossValidate.toJSON();
289+
const net = crossValidate.fromJSON(json);
290+
```
291+
292+
An example of using cross validate can be found in [examples/cross-validate.js](examples/cross-validate.js)
293+
294+
### Train Stream
295+
Streams are a very powerful tool in node for massive data spread across processes and are provided via the brain.js api in the following way:
296+
```js
297+
const net = new brain.NeuralNetwork();
298+
const trainStream = new brain.TrainStream({
299+
neuralNetwork: net,
300+
floodCallback: function() {
301+
flood(trainStream, data);
302+
},
303+
doneTrainingCallback: function(stats) {
304+
// network is done training! What next?
305+
}
306+
});
307+
308+
// kick it off
309+
readInputs(trainStream, data);
310+
311+
function readInputs(stream, data) {
312+
for (let i = 0; i < data.length; i++) {
313+
stream.write(data[i]);
314+
}
315+
// let it know we've reached the end of the inputs
316+
stream.endInputs();
317+
}
318+
```
319+
320+
An example of using train stream can be found in [examples/stream-example.js](examples/stream-example.js)
321+
277322
# Methods
278323
### train
279324
The output of `train()` is a hash of information about how the training went:
@@ -341,7 +386,7 @@ The network now has a [WriteStream](http://nodejs.org/api/stream.html#stream_cla
341386

342387

343388
### Example
344-
Refer to [`stream-example.js`](./examples/cli/stream-example.js) for an example on how to train the network with a stream.
389+
Refer to [`stream-example.js`](examples/stream-example.js) for an example on how to train the network with a stream.
345390

346391

347392
### Initialization

0 commit comments

Comments
 (0)