Use XGBoost to predict the survival of Titanic passengers.

[Instructions]

1_train.ipynb

Set the parameters:

• train_input_filename: input data file path

• model_filename: the path of the output prediction file

• scaler_filename: output normalized file path

• train_output_filename: the path of the output prediction file

• modelEstimators: the number of Estimators

After the setting is completed, it can be executed.

2. 2_inference.ipynb

Set the parameters parameter:

• inference_input_fileName: input data file path

• model_fileName: input model file path

• scaler_filename: input normalized file path

• inference_output_fileName: the path of the output prediction file

After the setting is completed, it can be executed.

After execution, you can see the results of XGBoost inference.

Jupyter-Data-XGBoost-Classification-inference.png

3. 3_inference_api.ipynb

Use Web API to perform inferences.

4. 4_inference_api_browser.ipynb

Open the browser to use the API.

This SDK is built in AppForAI - AI Dev Tools.

Purchase license separately: USD 600, permanent authorization, single APP authorization, single machine authorization, one-year activation, one-year download, one-year update, one-year email technical support.