XOR

script.js

// Reference
// https://github.com/mattcam/tfjs_xor_example
const model = tf.sequential();
model.add(tf.layers.dense({ units: 10, activation: "sigmoid", inputShape: [2] }));
model.add(tf.layers.dense({ units: 1, activation: "sigmoid" }));
model.compile({ optimizer: "rmsprop", loss: "meanSquaredError" });

const trainingData = tf.tensor2d([[0, 0], [0, 1], [1, 0], [1, 1]]);
const targetData = tf.tensor2d([[0], [1], [1], [0]]);

console.log("Learning...");

// Let's change the value of epochs and see what happens
// epochs: The number of times to iterate over the training data arrays
// epochsの値を変更して何が起こるかみてみよう
// epochs：トレーニング用データ配列を反復処理する回数
model.fit(trainingData, targetData, { epochs: 100 }).then(history => {
  console.log("Finished!");
  console.log("loss = " + history.history.loss[0]);

  model.predict(trainingData).print();
});

scripts

<script src="https://cdnjs.cloudflare.com/ajax/libs/tensorflow/0.12.5/tf.min.js"></script>

xor.markdown

XOR

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