Machine Learning - Multivariate Regression

Iya, yadda biliyyar lissan kama yadda yadda lissan biliyyar lissan.

Iya, yadda biliyyar lissan kama yadda yadda lissan biliyyar lissan. Iya, yadda biliyyar lissan kama yadda yadda lissan biliyyar lissan. Iya, yadda biliyyar lissan kama yadda yadda lissan biliyyar lissan.

Kai fannin dace dake, anan dake ba'a ga'a dake kanawa dake bayan dake. Anan ba'a ga'a dake kanawa dake bayan dake. Anan ba'a ga'a dake kanawa dake bayan dake.

Car Model Volume Weight CO2
Toyota Aygo 1000 790 99
Mitsubishi Space Star 1200 1160 95
Skoda Citigo 1000 929 95
Fiat 500 900 865 90
Mini Cooper 1500 1140 105
VW Up! 1000 929 105
Skoda Fabia 1400 1109 90
Mercedes A-Class 1500 1365 92
Ford Fiesta 1500 1112 98
Audi A1 1600 1150 99
Hyundai I20 1100 980 99
Suzuki Swift 1300 990 101
Ford Fiesta 1000 1112 99
Honda Civic 1600 1252 94
Hundai I30 1600 1326 97
Opel Astra 1600 1330 97
BMW 1 1600 1365 99
Mazda 3 2200 1280 104
Skoda Rapid 1600 1119 104
Ford Focus 2000 1328 105
Ford Mondeo 1600 1584 94
Opel Insignia 2000 1428 99
Mercedes C-Class 2100 1365 99
Skoda Octavia 1600 1415 99
Volvo S60 2000 1415 99
Mercedes CLA 1500 1465 102
Audi A4 2000 1490 104
Audi A6 2000 1725 114
Volvo V70 1600 1523 109
BMW 5 2000 1705 114
Mercedes E-Class 2100 1605 115
Volvo XC70 2000 1746 117
Ford B-Max 1600 1235 104
BMW 2 1600 1390 108
Opel Zafira 1600 1405 109
Mercedes SLK 2500 1395 120

我们可以根据发动机排量的大小预测汽车的二氧化碳排放量，但是通过多元回归，我们可以引入更多变量，例如汽车的重量，以使预测更加准确。

工作原理

在 Python 中，我们拥有可以完成这项工作的模块。首先导入 Pandas 模块：

import pandas

Pandas 模块允许我们读取 csv 文件并返回一个 DataFrame 对象。

此文件仅用于测试目的，您可以在此处下载：cars.csv

df = pandas.read_csv("cars.csv")

然后列出独立值，并将这个变量命名为 X。

将相关值放入名为 y 的变量中。

X = df[['Weight', 'Volume']]
y = df['CO2']

Tishi:Changguan, jiang duanliu zhi liebiao mingming daoxie XJuezhong xianxiang zhi liebiao mingming xiaoxie y.

Wome jiang shi yong sklearn mo kuai zhong de yi xie fangfa, yin ci women ye bixu daoruan zhe ge mo kuai:

from sklearn import linear_model

Zai sklearn mo kuai zhong, women jiang shi yong LinearRegression() Fangfa chuangjian yi ge xianxing huigui duixiang.

Zhege duixiang you yi ge mingcheng fit() de fangfa, zhege fangfa jiang duanliu zhi he zhongdu zhi danyu cengduo, yong miaoshu zhe zhong guanxi de shu ju tianrui huigui duixiang:

regr = linear_model.LinearRegression()
regr.fit(X, y)

Xianzai, women youle yi ge huigui duixiang, keyi genju qiche de zhongliang he paoliang yuce CO2 zhi:

# Yuce zhongliang wei 2300kg, paoliang wei 1300ccm de qiche de erdanban hua faliang:
predictedCO2 = regr.predict([[2300, 1300]])

Misali

Qing kan quan zhi shi lian:

import pandas
from sklearn import linear_model
df = pandas.read_csv("cars.csv")
X = df[['Weight', 'Volume']]
y = df['CO2']
regr = linear_model.LinearRegression()
regr.fit(X, y)
# Yuce zhongliang wei 2300kg, paoliang wei 1300ccm de qiche de erdanban hua faliang:
predictedCO2 = regr.predict([[2300, 1300]])
print(predictedCO2)

Nimci:

[107.2087328]

Ayyan Yana Gudana

Wome yuce, pei bei 1.3 shi liu motoru, zhongliang wei 2300 qianjin de qiche, mei xing 1 gongli, jiu hui fangshi yue 107 g erdanban hua.

Xishu

Xishu shi miaoshu yu weizhi bianliang guanxi de yuanzi.

Lai li: x Shi bianliang, zhi 2x Shi x de liang bei.x Shi weizhi bianliang, shu zi 2 Shi xishu.

Zai zhege qingkuang xia, women kengqiu zhongliang xiangdui CO2 de xishu zhi, yu riwei xiangdui CO2 de xishu zhi. Women de daanwen gaoxiang women, ruzhi women zengjia huo jianshao yige duanliu zhi, jiang xiangshen me.

Misali

Dayin huigui xiangguan duixiang de xishu zhi:

import pandas
from sklearn import linear_model
df = pandas.read_csv("cars.csv")
X = df[['Weight', 'Volume']]
y = df['CO2']
regr = linear_model.LinearRegression()
regr.fit(X, y)
print(regr.coef_)

Nimci:

[0.00755095 0.00780526]

Ayyan Yana Gudana

Jieguo shuoming

Jieguo shuzu biaoshi zhongliang he paoliang de xishu zhi.

Weight: 0.00755095
Volume: 0.00780526

Iyane na zaiyawa, idanin aiki yuwa 1g, kai CO2 faliya ga yuwa 0.00755095g.

Idanin kai aiki na motoru (kongju) yuwa 1 ccm, kai CO2 faliya ga yuwa 0.00780526g.

我认为这是一个合理的猜测，但还是请进行测试！

我们已经预言过，如果一辆配备 1300ccm 发动机的汽车重 2300 千克，则二氧化碳排放量将约为 107 克。

如果我们增加 1000g 的重量会怎样？

Misali

Kopiyar misali na daidai, amma kuma sa rufi daga 2300 zuwa 3300:

import pandas
from sklearn import linear_model
df = pandas.read_csv("cars.csv")
X = df[['Weight', 'Volume']]
y = df['CO2']
regr = linear_model.LinearRegression()
regr.fit(X, y)
predictedCO2 = regr.predict([[3300, 1300]])
print(predictedCO2)

Nimci:

[114.75968007]

Ayyan Yana Gudana

A na iya nuna, wanda ke da injin 1.3 liters, kuma rufi 3.3 ton, kowane kilomita ayyan ya tsara kimanin 115 gram carbon dioxide.

Wannan ya nufin in kofin 0.00755095 shine na hankali:

107.2087328 + (1000 * 0.00755095) = 114.75968