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RSS订阅原创 随机森林降维
import pandas as pdimport numpy as npimport matplotlib.pyplot as pltfrom sklearn.ensemble import RandomForestRegressorfrom sklearn.feature_selection import SelectFromModel# read the datatrain=pd.read_csv("xxx.csv")usedcols=['xxx', 'xxx','xxx']df =
2022-05-29 09:05:39
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原创 PCA降维
from sklearn.decomposition import PCAimport pandas as pdimport numpy as nptrain=pd.read_csv("xxx.csv")usedcols=['xxx','xxx']df = pd.DataFrame(train,columns=usedcols)pca = PCA(n_components=2)pca_result = pca.fit_transform(df)
2022-05-28 09:57:35
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原创 ValueError: Shape (6134, 30, 200) must have rank 0
原因：tensorflow版本不对应tensorflow2.0以上的版本用法： tf.concat(outputs,1)tensorflow2.0以下的版本用法：tf.concat(1,outputs)
2022-05-16 20:48:25
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