集成学习算法:梯度提升与随机森林在葡萄酒质量预测中的应用
梯度提升算法在多变量问题中的应用
梯度提升是一种强大的集成学习技术,可用于预测葡萄酒质量。以下是使用Python实现梯度提升算法预测葡萄酒质量的代码:
__author__ = 'mike-bowles'
import urllib2
import numpy
from sklearn import tree
from sklearn.tree import DecisionTreeRegressor
import random
from math import sqrt
import matplotlib.pyplot as plot
# 读取数据
target_url = "http://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-red.csv"
data = urllib2.urlopen(target_url)
xList = []
labels = []
names = []
firstLine = True
for line in data:
if firstLine:
names = line.strip().split(";")
firstLine = False
else:
row = line.strip().split(";")
labels.append(float(row[-1]))
row.pop()
floatRow = [float
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