TensorFlow.js机器学习预测鸢尾花种类

<script src="script.js"></script>

import {getIrisData, IRIS_CLASSES} from "./data.js";
window.onload = () => {
    // 加载数据
    const [xTrain, yTrain, xTest, yTest] = getIrisData(0.2);
    // 打印查看数据集
    xTrain.print();
    yTrain.print();
    xTest.print();
    yTest.print();
    // 打印鸢尾花种类类别
    console.log(IRIS_CLASSES);
}

// 定义网络模型
const model = tf.sequential();
// 添加隐藏层
model.add(tf.layers.dense({
    units: 10,
    inputShape: [xTrain.shape[1]],
    activation: 'relu'
}));
// 添加输出层 
model.add(tf.layers.dense({
    units: 3,
    activation: 'softmax'
}));
// 配置模型
model.compile({
    loss: "categoricalCrossentropy",
    optimizer: tf.train.adam(0.1),
    metrics: ['accuracy']
});

await model.fit(xTrain, yTrain,{
    epochs: 100,
    batchSize: 32,
    validationData: [xTest, yTest],
    callbacks: tfvis.show.fitCallbacks(
         {name: '训练效果'},
         ['loss', 'val_loss', 'acc', 'val_acc'],
         {callbacks: ['onEpochEnd']}
    )
}); 

<form action="" onsubmit="predict(this); return false">
    花萼长度：<input type="text" name="a"><br>
    花萼宽度：<input type="text" name="b"><br>
    花瓣长度：<input type="text" name="c"><br>
    花瓣宽度：<input type="text" name="d"><br>
    <button type="submit">预测</button>
</form>

 window.predict = (form) => {
        // 将表单获取的到数据转成Tensor
        const input = tf.tensor([[
            form.a.value * 1,
            form.b.value * 1,
            form.c.value * 1,
            form.d.value * 1,
        ]]);
        // 预测
        const pred = model.predict(input);
        alert(`预测结果：${IRIS_CLASSES[pred.argMax(1).dataSync(0)]}`)
    }