XGBoost feature_names不匹配时间序列

Question

我试图预测股票趋势，其中1是股票上涨，0是股票在特定的一天下跌。我的输入特征是收盘价，成交量，当天的趋势，我的输出是第二天的趋势。当应用XGBClassifier()时，我遇到一个错误:

ValueError                                Traceback (most recent call last)
<ipython-input-101-d14cdb520e55> in <module>
1 val = np.array(test[0, 0]).reshape(1, -1)
2 
----> 3 pred = model.predict(val)
4 print(pred[0])
~/opt/anaconda3/lib/python3.8/site-packages/xgboost/sklearn.py in predict(self, data, output_margin, ntree_limit, validate_features, base_margin)
968         if ntree_limit is None:
969             ntree_limit = getattr(self, "best_ntree_limit", 0)
--> 970         class_probs = self.get_booster().predict(
971             test_dmatrix,
972             output_margin=output_margin,
~/opt/anaconda3/lib/python3.8/site-packages/xgboost/core.py in predict(self, data, output_margin, ntree_limit, pred_leaf, pred_contribs, approx_contribs, pred_interactions, validate_features, training)
1483 
1484         if validate_features:
-> 1485             self._validate_features(data)
1486 
1487         length = c_bst_ulong()
~/opt/anaconda3/lib/python3.8/site-packages/xgboost/core.py in _validate_features(self, data)
2058                             ', '.join(str(s) for s in my_missing))
2059 
-> 2060                 raise ValueError(msg.format(self.feature_names,
2061                                             data.feature_names))
2062 
ValueError: feature_names mismatch: ['f0', 'f1', 'f2', 'f3'] ['f0']
expected f2, f1, f3 in input data

我的代码如下:

def xgb_predict(train, val):
train = np.array(train)
x, y = train[:, :-1], train[:, -1] 
model = XGBClassifier()
model.fit(x, y)

val = np.array(val).reshape(1, -1)
pred = model.predict(val)
return pred[0]
xgb_predict(train, test[0, 0])

我在第8行收到一个错误。非常感谢你的帮助:)

编辑:包含数据样本

Answer 1

测试数据的列选择必须像您对列车数据所做的那样完成。这意味着你的最后一行应该是:

xgb_predict(train, test[0, :-1])

所以你可以选择所有的列/特征，但最后一个是目标值。