官术网_书友最值得收藏!

Running the application

To run the application the process is nearly identical to Chapter 2's sample application. To iterate more quickly, the debug configuration automatically passes in the included sampledata.csv file as a command-line parameter:

Going forward, due to the increasing complexity of the applications, all sample applications will have this preset:

  1. To run the training on the command line as we did in Chapter 1, Getting Started with Machine Learning and ML.NET, simply pass in the following command (assuming you are using the included sample dataset):
PS chapter03\bin\Debug\netcoreapp3.0> .\chapter03.exe train ..\..\..\Data\sampledata.csv 
Loss Function: 324.71
Mean Absolute Error: 12.68
Mean Squared Error: 324.71
RSquared: 0.14
Root Mean Squared Error: 18.02

Note the expanded output to include several metric data pointswe will go through what each one of these means at the end of this chapter.

  1. After training the model, build a sample JSON file and save it as input.json:
{
"durationInMonths": 0.0,
"isMarried": 0,
"bsDegree": 1,
"msDegree": 1,
"yearsExperience": 2,
"ageAtHire": 29,
"hasKids": 0,
"withinMonthOfVesting": 0,
"deskDecorations": 1,
"longCommute": 1
}
  1. To run the model with this file, simply pass in the filename to the built application and the predicted output will show:
PS chapter03\bin\Debug\netcoreapp3.0> .\chapter03.exe predict input.json 
Based on input json:
{
"durationInMonths": 0.0,
"isMarried": 0,
"bsDegree": 1,
"msDegree": 1,
"yearsExperience": 2,
"ageAtHire": 29,
"hasKids": 0,
"withinMonthOfVesting": 0,
"deskDecorations": 1,
"longCommute": 1
}

The employee is predicted to work 22.82 months

Feel free to modify the values and see how the prediction changes based on the dataset that the model was trained on.  A few areas of experimentation from this point might be to do the following:

  • Add some additional features based on your own experience.
  • Modify sampledata.csv to include your team's experience.
  • Modify the sample application to have a GUI to make running predicts easier.
主站蜘蛛池模板: 怀宁县| 深圳市| 晋江市| 贵德县| 曲周县| 工布江达县| 平和县| 九台市| 朔州市| 桂东县| 大丰市| 双柏县| 鹰潭市| 延边| 信阳市| 威宁| 潍坊市| 噶尔县| 开原市| 镇远县| 桃园市| 自贡市| 瓦房店市| 赣州市| 图片| 郧西县| 子长县| 遂昌县| 枝江市| 增城市| 玉林市| 柯坪县| 共和县| 德保县| 孟津县| 利辛县| 池州市| 灵石县| 府谷县| 博客| 顺平县|