我有一个数据集，我已经绘制，以显示在时间x的销售额超过价格y。我用一个模型来预测这段时间内的价格y。
然而，似乎无论我加上或减去多少复杂度，我都不能让模型将向下倾斜的梯度作为其最终输出的一部分？
我怎样才能做到这一点？
输出示例：

模型

function createModel() {
            const model = tf.sequential();

            //adding a layer
            model.add(tf.layers.dense({
                units: 5, //number of nodes in layer
                useBias: true, //adds a bias parameter 
                activation: 'tanh', //activation function
                inputDim: 1, //amount of inputs
            }));

            //not an input layer so has no inputDim property
            model.add(tf.layers.dense({
                units: 10, //number of nodes in layer
                useBias: true, //adds a bias parameter 
                activation: 'softmax', //activation function
            }));

            model.add(tf.layers.dense({
                units: 10, //number of nodes in layer
                useBias: true, //adds a bias parameter 
                activation: 'sigmoid', //activation function
            }));

            model.add(tf.layers.dense({
                units: 5, //number of nodes in layer
                useBias: true, //adds a bias parameter 
                activation: 'tanh', //activation function
            }));

            //output layer with one node
            model.add(tf.layers.dense({
                units: 1, //number of nodes in layer
                useBias: true, //adds a bias parameter 
                activation: 'tanh', //activation function
            }));

            const optimizer = tf.train.adam(0.1); //parameter = learning rate

            model.compile({
                loss: 'meanSquaredError',
                optimizer
            })

            return model;
        }