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Prediction Models

Overview

The Insights Hub Quality Prediction application provides a user interface for creating, training and evaluating the data using a relevant machine and processes data to produce the Machine Learning models called as Prediction models.

The Prediction model initially created is in the "Draft" status, by default. Following successful model training, it is saved as a new model version and its status changes to "In Training" and is referred as "Training Board". Once the model is run with real-time predictions, the status of the model is now "Running" and is referred as "Operator Board". The prediction models are displayed as shown in the below image.

Prediction models intro

① Displays the total number of Prediction Models
② Displays the total number of Training Models
③ Displays the total number of Running Models

All the available models can be accessed by selecting “See all Prediction Models”. "Training and Running" models can be accessed by selecting “See details” for the corresponding models as shown in the below image.

Prediction models intro

Prediction Model Workflow

This workflow outlines the key steps for setting up models and generating prediction results:

Prediction
Models
Prediction...
Setup model
Setup model
Generation and evaluation of prediction results
Generation and evalu...
Evaluate the Model training
Evaluate the Model trai...
Create multiple mo...Create model
Generation of model  prediction
Generation of model...
 Evaluation of prediction results
Evaluation of predi...
Prediction
Models
Prediction...
Setup model
Setup model
Create model
Create model
Create multiple models
Create multiple mo...
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Parameters and limits for the Prediction Models

Parameters and limits for the Prediction Models are listed below:

Parameter Limit
Number of Features for Training 15
Number of data points for quality data (rows) 20,000
Number of models 3 x Number of max active models
Number of active models Quota parameter(Initial value is 3)
Inference frequency 60 sec
Inference time window 7 days
Inference late arrival window 1 hour
Inference data points of all variables ¹ in inference time window 10,000,000 (15 points per second for 7 days)
Training time window 1 year
Training data points of all variable 10,000,000
Features in preview 15
Filter definitions 5

Last update: January 21, 2025