文章目录
线性回归代码实现
代码实现
代码语言：javascript
复制#! /bin/python3
# -*-encoding="utf-8"-*-
# __Author__ ="ErrolYan"
# __Time__="2018.12.23"
from argparse import Namespace
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from sklearn.linear_model.stochastic_gradient import SGDRegressor
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import train_test_split
import matplotlib.pyplot as plt
# Arguments
args = Namespace(
seed=1234,
data_file="sample_data.csv",
num_samples=100,
train_size=0.75,
test_size=0.25,
num_epochs=100,
)
# Set seed for reproducability
np.random.seed(args.seed)
# Generate synthetic data Function
def generate_data
