【Python】逻辑回归（二分类）

Tensorflow实现逻辑回归-二分类

import tensorflow as tf
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

# 逻辑回归 - 二分类
data = pd.read_csv('credit-a.csv', header=None)

print(data.iloc[:, -1].value_counts())

x = data.iloc[:, :-1]
y = data.iloc[:, -1].replace(-1, 0)

model = tf.keras.Sequential()
model.add(tf.keras.layers.Dense(4, input_shape=(15,), activation='relu'))
model.add(tf.keras.layers.Dense(4, activation='relu'))
model.add(tf.keras.layers.Dense(1, activation='sigmoid'))

print(model.summary())

model.compile(optimizer='adam',
              loss='binary_crossentropy',
              metrics=['acc'])

history = model.fit(x, y, epochs=100)

plt.plot(history.epoch, history.history.get('loss'))
plt.show()

plt.plot(history.epoch, history.history.get('acc'))
plt.show()