模型的特征数量必须与输入匹配 [英] Number of features of the model must match the input

问题描述

出于某种原因，此数据集的要素被解释为行，模型n_features为16，输入n_features为18189"，其中18189是行数，16是正确的要素列表.

For some reason the features of this dataset is being interpreted as rows, "Model n_features is 16 and input n_features is 18189" Where 18189 is the number of rows and 16 is the correct feature list.

可疑代码在这里:

for var in cat_cols:
    num = LabelEncoder()
    train[var] = num.fit_transform(train[var].astype('str'))
    train['output'] = num.fit_transform(train['output'].astype('str'))

for var in cat_cols:
    num = LabelEncoder()
    test[var] = num.fit_transform(test[var].astype('str'))
    test['output'] = num.fit_transform(test['output'].astype('str'))


clf = RandomForestClassifier(n_estimators = 10)

xTrain = train[list(features)].values
yTrain = train["output"].values

xTest = test[list(features)].values
xTest = test["output"].values 

clf.fit(xTrain,yTrain)
clfProbs = clf.predict(xTest)#Error happens here.

有人有什么主意吗?

示例培训日期csv

tr4,42,"JobCat4","divorced","tertiary","yes",2,"yes","no","unknown",5,"may",0,1,-1,0,"unknown","TypeA"

示例测试数据csv

tst2,47,"JobCat3","married","unknown","no",1506,"yes","no","unknown",5,"may",0,1,-1,0,"unknown",?

推荐答案

您有一个小的错字-您创建了变量xTest，然后立即将其覆盖为不正确的内容.将有问题的行更改为:

You have a small typo - you created the variable xTest and then are immediately overwriting to something incorrect. Change the offending lines to:

xTest = test[list(features)].values
yTest = test["output"].values 

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