- Hands-On Machine Learning with ML.NET
- Jarred Capellman
- 121字
- 2021-06-24 16:43:30
Running the example
To run both the training and prediction, simply build the project and then pass in the appropriate data.
For training, you can use the included sampledata.csv file or create your own. We will do this by opening a PowerShell window and passing in the relative path:
.\chapter02.exe train ..\..\..\Data\sampledata.csv
Area Under Curve: 100.00%
Area Under Precision Recall Curve: 100.00%
Accuracy: 100.00%
F1Score: 100.00%
Positive Recall: 1
Negative Recall: 1
Once the model is built, you can run the prediction as follows:
.\chapter02.exe predict "bad"
Based on "bad", the feedback is predicted to be:
Negative at a 64% confidence
Feel free to try various phrases to test the efficacy of the model, and congratulations on training your first model!
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