出现以下错误未知标签类型:“连续”?

时间:2020-03-07 14:34:19

标签: python-3.x machine-learning scikit-learn

根据研究,我已经做到了,因为我的特征中有浮动。 我无法显示我的数据,因为它是机密的,但它是这样的:

功能1(int),功能2,3(猫一热编码),功能4,5,6(浮动)

代码

#Importing dependencies
import numpy as np
import pandas as pd
import glob
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
from sklearn.model_selection import RandomizedSearchCV
#Reading multiple CSV files into 1 DF 
list_csv= []
for file in glob.glob('C:/Users/Muhammad Ashraf Khan/Documents/Projects/*.csv'):
    df = pd.read_csv(file, index_col=None, header=0)
    list_csv.append(df)

data = pd.concat(list_csv, axis=0, ignore_index=True)
#input features
Features=fd.drop("Target",axis=1)
#output feature
y=fd["Target"]
print(y.shape)
#One hot encoding 
from sklearn.preprocessing import OneHotEncoder,LabelEncoder
ohe=OneHotEncoder()
encoded_var=ohe.fit_transform(Features[["col 2","col 3"]]).toarray()
from sklearn.compose import make_column_transformer
column_trans=make_column_transformer(
(OneHotEncoder(),["col 2","col 3"]))
X=column_trans.fit_transform(Features)


#Feature Importance
from sklearn.ensemble import ExtraTreesClassifier
model = ExtraTreesClassifier()
model.fit(X,y)
print(model.feature_importances_) 
feat_importances = pd.Series(model.feature_importances_, index=X.columns)
feat_importances.nlargest(10).plot(kind='barh')

0 个答案:

没有答案
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