线性回归神经网络Tensorflow Keras Python程序

我写了一本小册子 “线性回归神经网络Tensorflow Keras Python程序”

输入数据集是 y=mx+c直线数据

预测的y值不正确，给出了一种水平线 值，而不是具有某些坡度的线

我用tensorflow、Keras和 Jupyter笔记本

请做什么来修复此程序

谢谢并致以最良好的祝愿， SSJ

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
n2 = 50
count = 20
n4 = n2 + count
p = 100
m = 10
c  = 5
x = np.linspace(n2, n4, p)
y = m * x + c
x
y
plt.scatter(x,y)
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers
from tensorflow.keras.layers.experimental import preprocessing
x_normalizer = preprocessing.Normalization(input_shape=[1,])
x_normalizer.adapt(x)
x_normalized = x_normalizer(x)
y_normalizer = preprocessing.Normalization(input_shape=[1,])
y_normalizer.adapt(y)
y_normalized = x_normalizer(y)
y_model = tf.keras.Sequential([
    y_normalizer,
    layers.Dense(1)
])
y_model.compile(optimizer='rmsprop', loss='mse', metrics = ['mae'])
y_hist = y_model.fit(x, y, epochs=100, verbose=0, validation_split = 0.2)
hist = pd.DataFrame(y_hist.history)
hist['epoch'] = y_hist.epoch
hist.head()
hist.tail()
xin = [51,53,59,64]
ypred = y_model.predict(xin)
ypred
plt.scatter(x, y)
plt.scatter(xin, ypred, color = 'r')
plt.grid(linestyle = '--')