英文:
how make kmeans on specific columns?
问题
我想对我的数据集中的特定列执行K均值。由于这些是分类数据，我计划对其进行独热编码。现在我想知道是否可以对特定列执行K均值，并显示结果（例如一个组的结果）以及所有列？
例如，我有col1、col2和col3，对col2和col3执行K均值，这些列已进行了独热编码，并显示包括col1、col2和col3在内的结果。
我希望我已经清楚地表达了我的问题。
英文:
I would like to do a K-means on specific columns of my data set.
As these are categorical data, I plan to do a onehot_encoding on it. Now I would like to know if it is possible to do K-means on specific columns and display the results (of a group for example) with all the columns?
For example i have col1, col2 and col3, K-means on col2 and col3which are onehot_encoded and display results with col1, col2 and col3.
I hope I have clearly expressed my concern
答案1
得分: 4
这是kmeans的基本文档遵循的部分：
from sklearn.cluster import KMeans
#在这里选择你的列
X = df[['col1', 'col2', 'col3']]
kmeans = KMeans(n_clusters=2, random_state=0).fit(X)
#这将为您提供分组
kmeans.predict(X)
因此，kmeans预测命令将为您提供分组，您可以将其添加到原始数据中。
英文:
This follows the basic documentation of kmeans:
from sklearn.cluster import KMeans
#here you select your columns
X = df[['col1', 'col2', 'col3']]
kmeans = KMeans(n_clusters=2, random_state=0).fit(X)
#this will give you the groups back
kmeans.predict(X)
So the kmeans predict command will give you the group back which you can add to your original data.
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