Resuming training on Neural Network

[knapcio]

Hi, Neural Network gives me weird results. Maybe I miss something. Please help.

What is wrong?

Neural Network result is incorrect.

Where does it happen?

I'm running 2.0.0-alpha.12 on Node 13 and Mac.

How do we replicate the issue?

Firstly I tried:

const brain = require('brain.js');

const net = new brain.NeuralNetwork();

const trainingData = {
	input: { a: 0, b: 1 },
	output: { good: 1 },
};

net.train(trainingData);

const trainingData2 = {
	input: { a: 1, b: 0 },
	output: { bad: 1 },
};

net.train(trainingData2);

const result = net.run({ a: 0, b: 1 });

console.log(result);
// Output: { good: 0.060428500175476074 }
// I expect: { good: 1 }

Then tried serialising as advised but still doesn't work:

const brain = require('brain.js');

// first  training
const trainingData = {
	input: { a: 0, b: 1 },
	output: { good: 1 },
};
const net = new brain.NeuralNetwork();
net.train(trainingData);
const stringifiedNet = JSON.stringify(net.toJSON());

// second training
const trainingData2 = {
	input: { a: 1, b: 0 },
	output: { bad: 1 },
};
const net2 = new brain.NeuralNetwork();
net2.fromJSON(JSON.parse(stringifiedNet));
net2.train(trainingData2);
const stringifiedNet2 = JSON.stringify(net2.toJSON());

// prediction
const net3 = new brain.NeuralNetwork();
net3.fromJSON(JSON.parse(stringifiedNet2));
const result = net3.run({
	a: 0,
	b: 1,
});
console.log(result);
// Output: { good: 0.07364676147699356 }
// I expect: { bad: 0, good: 1 }

const result2 = net3.run({
	a: 1,
	b: 0,
});
console.log(result2);
// Output: { good: 0.07043380290269852 }
// I expect: { bad: 1, good: 0 }

How important is this (1-5)?

4

Expected behavior (i.e. solution)

I expect NN to return other results (described in code comments).

Other Comments

You guys do an awesome job building brain.js!

EDIT: Seen this comment on StackOverflow: The keepNetworkIntact has been renamed to reinforce but can't see this property in INeuralNetworkTrainingOptions

EDIT2: I read somewhere I should pass all data every time I run train. Is there any way around it? I train the NN every day with new daily statistics. Seems insane to have to calculate them every time for all the previous days (i.e. past 2 years).

[robertleeplummerjr]

Your training data is in the wrong format. Supply an array of objects.

const trainingData = [{
	input: { a: 0, b: 1 },
	output: { good: 1 },
}];

net.train(trainingData);

[knapcio]

Thanks for the prompt response. I really appreciate. it.

Sorry, I also tried with arrays and still doesn't work:

const brain = require('brain.js');

const net = new brain.NeuralNetwork();

const trainingData = [{
	input: { a: 0, b: 1 },
	output: { good: 1 },
}];

net.train(trainingData);

const trainingData2 = [{
	input: { a: 1, b: 0 },
	output: { bad: 1 },
}];

net.train(trainingData2);

const result = net.run({ a: 0, b: 1 });

console.log(result);
// Output: { good: 0.0637415423989296 }

and the second way:

const brain = require('brain.js');

// first  training
const trainingData = [{
	input: { a: 0, b: 1 },
	output: { good: 1 },
}];
const net = new brain.NeuralNetwork();
net.train(trainingData);
const stringifiedNet = JSON.stringify(net.toJSON());

// second training
const trainingData2 = [{
	input: { a: 1, b: 0 },
	output: { bad: 1 },
}];
const net2 = new brain.NeuralNetwork();
net2.fromJSON(JSON.parse(stringifiedNet));
net2.train(trainingData2);
const stringifiedNet2 = JSON.stringify(net2.toJSON());

// prediction
const net3 = new brain.NeuralNetwork();
net3.fromJSON(JSON.parse(stringifiedNet2));
const result = net3.run({
	a: 0,
	b: 1,
});
console.log(result);
// Output: { good: 0.060673292726278305 }

const result2 = net3.run({
	a: 1,
	b: 0,
});
console.log(result2);
// Output: { good: 0.070485919713974 }

[robertleeplummerjr]

Reproduced this issue here: https://observablehq.com/@robertleeplummerjr/brain-js-issue-514

[knapcio]

I actually believe there are 2 different issues.

The first one is what you described on observablehq - undefined output value.

The second one is resuming a training. Please consider the following code:

const brain = require('brain.js');

// first  training
const trainingData = [{
	input: { a: 0, b: 1 },
	output: { good: 1, bad: 0.1 },
}];
const net = new brain.NeuralNetwork();
net.train(trainingData);
const stringifiedNet = JSON.stringify(net.toJSON());

// second training
const trainingData2 = [{
	input: { a: 1, b: 0 },
	output: { bad: 1, good: 0.1 },
}];
const net2 = new brain.NeuralNetwork();
net2.fromJSON(JSON.parse(stringifiedNet));
net2.train(trainingData2);
const stringifiedNet2 = JSON.stringify(net2.toJSON());

// prediction
const net3 = new brain.NeuralNetwork();
net3.fromJSON(JSON.parse(stringifiedNet2));
const result = net3.run({
	a: 0,
	b: 1,
});
console.log(result);
// Output: { good: 0.14621490240097046, bad: 0.9085853099822998 }

const result2 = net3.run({
	a: 1,
	b: 0,
});
console.log(result2);
// Output: { good: 0.1430644392967224, bad: 0.9107764959335327 }

Even if I provide the full output in every training (both good and bad) it still gives a wrong result in the first prediction (good should be closer to 1 when bad should be small)

[ehortle]

Hi guys, I have been trying brain.js and am experiencing this as well.

This seems to be falling over at the first hurdle - it seems basically to be an error in the most elementary case, and for my implementation of brain.js it's important that this works. Does this basically mean that for all live installations of brain.js, the neural network is not actually working as specified in the docs? This seems to be an extremely high priority bug to me.

Hoping you can comment on the possibility of a fix soon and thanks for all the work on the project 😄

[robertleeplummerjr]

It is a very high priority issue, and I plan on looking at it tomorrow morning.

[robertleeplummerjr]

I am not sure I see any issue, though I've tried to reproduce what you mention @knapcio: https://observablehq.com/@robertleeplummerjr/brain-js-issue-514/2

You mention:

Even if I provide the full output in every training (both good and bad) it still gives a wrong result in the first prediction (good should be closer to 1 when bad should be small)

Yet your training data is exactly:

const trainingData2 = [{
	input: { a: 1, b: 0 },
	output: { bad: 1, good: 0.1 },
}];

Which seems to correlate with an a of 1 should produce a high bad and a low good.

When you call:

net2.train(trainingData2);

Are you expecting the previous training data to perhaps remain intact inside the net? If so, you need to simply do this:

net2.train([...trainingData, ...trainingData2]);

[robertleeplummerjr]

@ehortle can you share your use example for more context?

[knapcio]

Ok, I see, so it seems like it's just not possible to resume a training on an already trained net.

Are you expecting the previous training data to perhaps remain intact inside the net?

Not sure what it exactly means, but maybe yes. Here you mention I could achieve it with toJson, but it doesn't seem to work.

As I mentioned in EDIT2: I need to train my network on a daily basis. Every day, I have to pull some data from that single day and modify the current NN. It's impossible to train the network every day from scratch - too much data. I need to simply append the new training result to a previous one.

I don't know the brain.js implementation, but this is how I'd imagine it should work:

1. User trains NN which saves weights and number of samples (maybe it could save some kind of weight of the whole training).
2. Saves NN to JSON.
3. Then user can recreate the NN from JSON any time.
4. Now user can train the NN again and the new training output (weights, sample count etc) is merged with a previous one (possibly using previously mentioned weight of each training)
5. User runs a "prediction" function and it predicts basing on all past trainings.

Hope it all makes sense.