由于某种原因,该数据集的特征被解释为行,“模型 n_features 为 16,输入 n_features 为 18189”其中 18189 是行数,16 是正确的特征列表。
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.
有人有什么想法吗?
样本训练日期 csv
tr4,42,"JobCat4","divorced","tertiary","yes",2,"yes","no","unknown",5,"may",0,1,-1,0,"unknown","TypeA"
样本测试数据 csv
tst2,47,"JobCat3","married","unknown","no",1506,"yes","no","unknown",5,"may",0,1,-1,0,"unknown",?