英文:
Does XGBoost Classifier Model pay attention to all X-data entries when making the prediction? Or only same indexed X-data?
问题
以下是已翻译的部分：
"以下是一个虚构的示例，类似于Pandas数据框，用于存储我正在处理的数据并包含XGBoost分类器模型生成的预测值。"
"| X_Data | Target |"
"| -------- | -------- |"
"| 1 | ?? |"
"| 2 | Cell 4 |"
"在调用 XGBClassifier.predict(df['X_data']) 时，预测模型是否同时考虑了X_Data列中的两个值？还是只考虑了value = 1，因为目标预测列与value = 1的索引相同？"
"我希望我的预测模型在X_data中目标索引周围查看几个值...我已经开始使用 df["X_Data"].shift() 创建其他列，以防模型只查看了相同索引的数据，但不知道模型是否已经查看了这些数据条目。"
英文:
The following made up example is to resemble a Pandas Dataframe, which is storing the data I'm working with and housing my predicted values made by the XGBoost Classifier model
| X_Data | Target |
|---|---|
| 1 | ?? |
| 2 | Cell 4 |
when calling XGBClassifier.predict(df['X_data'])
Does the predictor model look at both values in column X_Data? or only value = 1 since the target predicted column is same index as value = 1?
I want my predictor to 'look' at several values around the target's index in X_data... I began to make other columns with df["X_Data"].shift() in case the model WAS 'looking' at same indexed data only, but didn't know if the model is looking at these data entries already.
答案1
得分: 1
XGBoost分类模型在进行预测时是否关注所有的X数据条目？
不是的。每一行都会被单独分类。
英文:
>Does XGBoost Classifier Model pay attention to all X-data entries when making the prediction?
No. Each row is classified separately.
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