Python类关联
我以前试过这个问题。但也许我必须保持简单。我有一个jaccard值,可以从0到1。我有两个类别,从1到7。这些类别值的每个组合都会产生另一个jaccard值。有没有什么方法可以找到分类号和信用卡价值之间的某种关联?所以,像类别1的值1总是给出一个高jaccard,而类别2的值2总是给出一个高jaccard,或者类别1的值2总是给出一个高jaccard,无论类别2的值是什么Python类关联,python,pandas,numpy,scipy,scikit-learn,Python,Pandas,Numpy,Scipy,Scikit Learn,我以前试过这个问题。但也许我必须保持简单。我有一个jaccard值,可以从0到1。我有两个类别,从1到7。这些类别值的每个组合都会产生另一个jaccard值。有没有什么方法可以找到分类号和信用卡价值之间的某种关联?所以,像类别1的值1总是给出一个高jaccard,而类别2的值2总是给出一个高jaccard,或者类别1的值2总是给出一个高jaccard,无论类别2的值是什么 import numpy as np #[category 1, category 2, jaccard] arra
import numpy as np
#[category 1, category 2, jaccard]
array1 = np.array([[1,1,0.1627]
[1,2,0.2993]
[1,3,0.1192]
[1,4,0.201 ]
[1,5,0.0678]
[1,6,0.2354]
[1,7,0.1921]
[2,1,0.1627]
[2,2,0.2993]
[2,3,0.1192]
[2,4,0.201 ]
[2,5,0.0678]
[2,6,0.2354]
[2,7,0.1921]
[3,1,0.1627]
[3,2,0.2993]
[3,3,0.1192]
[3,4,0.201 ]
[3,5,0.0678]
[3,6,0.2354]])
是一个很棒的python软件包,其中包含大量有用的统计/数据科学函数,如correlation
import pandas as pd
import numpy as np
array1 = np.array([[1,1,0.1627],
[1,2,0.2993],
[1,3,0.1192],
[1,4,0.201 ],
[1,5,0.0678],
[1,6,0.2354],
[1,7,0.1921],
[2,1,0.1627],
[2,2,0.2993],
[2,3,0.1192],
[2,4,0.201 ],
[2,5,0.0678],
[2,6,0.2354],
[2,7,0.1921],
[3,1,0.1627],
[3,2,0.2993],
[3,3,0.1192],
[3,4,0.201 ],
[3,5,0.0678],
[3,6,0.2354]])
df = pd.DataFrame(columns=["cat1", "cat2", "jaccard"], data=array1)
df.corr()
“class”,这是一个Python类,还是仅仅是您的值的名称?根据构造,您的数组将是
dtype
float。
# correlation output
cat1 cat2 jaccard
cat1 1.00000 -0.101380 -0.008720
cat2 -0.10138 1.000000 -0.109329
jacard -0.00872 -0.109329 1.000000