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mdsp trend-prediction Command


mdsp trend-prediction


mdsp trend-prediction --help

Alternative form:

mc trend-prediction

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


perform trend prediction (linear/polynomial) @


Parameter list:

Usage: mdsp trend-prediction|tp [options]

perform trend prediction (linear/polynomial) @

 -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


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


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

 mdsp tp --mode train -f data.json -i "temp,vibration" -o "quality" -d 2 trains quadratic fit function for f(temp, vibration) = quality 
 mdsp 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:

See Insights Hub API documentation for more information about Insights Hub APIs.


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