# xgboostlinearnode properties #

![XGBoost Linear node icon](https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/scripting_guide/clementine/images/pythonxgboostlinearnodeicon.png)XGBoost Linear© is an advanced implementation of a gradient boosting algorithm with a linear model as the base model\. Boosting algorithms iteratively learn weak classifiers and then add them to a final strong classifier\. The XGBoost Linear node in SPSS Modeler is implemented in Python\.

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xgboostlinearnode properties  

Table 1\. xgboostlinearnode properties

| `xgboostlinearnode` properties | Data type | Property description                                                                                                                                                                                                                                                                                                                                                                           |
| ------------------------------ | --------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `custom_fields`                | *boolean* | This option tells the node to use field information specified here instead of that given in any upstream Type node(s)\. After selecting this option, specify fields as required\.                                                                                                                                                                                                              |
| `target`                       | *field*   |                                                                                                                                                                                                                                                                                                                                                                                                |
| `inputs`                       | *field*   |                                                                                                                                                                                                                                                                                                                                                                                                |
| `alpha`                        | *Double*  | The alpha linear booster parameter\. Specify any number `0` or greater\. Default is `0`\.                                                                                                                                                                                                                                                                                                      |
| `lambda`                       | *Double*  | The lambda linear booster parameter\. Specify any number `0` or greater\. Default is `1`\.                                                                                                                                                                                                                                                                                                     |
| `lambdaBias`                   | *Double*  | The lambda bias linear booster parameter\. Specify any number\. Default is `0`\.                                                                                                                                                                                                                                                                                                               |
| `num_boost_round`              | *integer* | The num boost round value for model building\. Specify a value between `1` and `1000`\. Default is `10`\.                                                                                                                                                                                                                                                                                      |
| `objectiveType`                | *string*  | The objective type for the learning task\. Possible values are ﻿`reg:linear`,﻿ `reg:logistic`,﻿ `reg:gamma`,﻿ `reg:tweedie`, ﻿`count:poisson`, ﻿`rank:pairwise`, `binary:logistic`, or `multi`\. Note that for flag targets, only `binary:logistic` or `multi` can be used\. If `multi` is used, the score result will show the `multi:softmax` and `multi:softprob` XGBoost objective types\. |
| `random_seed`                  | *integer* | The random number seed\. Any number between `0` and `9999999`\. Default is `0`\.                                                                                                                                                                                                                                                                                                               |
| `useHPO`                       | *Boolean* | Specify `true` or `false` to enable or disable the HPO options\. If set to `true`, Rbfopt will be applied to find out the "best" One\-Class SVM model automatically, which reaches the target objective value defined by the user with the `target_objval` parameter\.                                                                                                                         |

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