MindSphere CLI: mdsp trend-prediction Command

Syntax:

mdsp trend-prediction

Help:

mdsp trend-prediction --help

Alternative form:

mc trend-prediction

(The CLI was using mc as default command name in older versions)

Description

perform trend prediction (linear/polynomial) @

Usage

Parameter list:

Usage: mc trend-prediction|tp [options]

perform trend prediction (linear/polynomial) @

Options:
  -f, --file                                       timeseries file (default: "timeseries-sample.mdsp.json")
  -m, --mode [train|predict|trainandpredict|list|read|delete]  mode see @ Additional Documentation (default: "list")
  -o, --output                                         output variables
  -i, --input                                           input variables (comma separated)
  -e, --modelid                                       modelid of the stored model for prediction
  -r, --predict                                       regression parameters for prediction (comma separated)
  -c, --predictfile                               regression parameters for prediction as timeseries
  -d, --degree [degree]                                        degree for linear / polynomial regression  (default: "1")
  -y, --retry                                          retry attempts before giving up (default: "3")
  -p, --passkey                                       passkey
  -v, --verbose                                                verbose output
  -h, --help                                                   display help for command

Examples

Here are some examples of how to use the mdsp trend-prediction command:


  Examples:

    mc trend-prediction --mode list 				 lists all trend prediction models
    mc trend-prediction --mode get --modelid 12345..ef 		 retrieves the trend prediction model from the mindsphere
    mc trend-prediction --mode delete --modelid 12345..ef 	 deletes the trend prediction model from the mindsphere
    mc tp --mode trendandpredict 				 training and prediction in one single step (see parameters below)

    mc tp --mode train -f data.json -i "temp,vibration" -o "quality" -d 2 		   trains quadratic fit function for f(temp, vibration) = quality 
    mc tp --mode predict --modelid 12345..ef -i "temp,vibration" -o "quality" -p "30,0.01" predict the quality with temp=30, vibration=0.01 using trained model

  Additional Documentation:

    https://developer.mindsphere.io/apis/analytics-trendprediction/api-trendprediction-basics.html

See MindSphere API documentation for more information about MindSphere APIs.

Further Information

The content of the community tools and libraries documentation pages is licensed under the MIT License.
Siemens API Notice applies.
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