Predictive Analytics
Now Reading
What is Deployment of Predictive Models ?

What is Deployment of Predictive Models ?

What is Deployment of Predictive Models ?
4.61 (92.17%) 23 ratings

Predictive Model Deployment : Predictive Model Deployment provides the option to deploy the analytical results in to every day decision making process, for automating the decision making process. The predictive models validation and deployment are time consuming activities, which takes months depending on the business scenarios. There are many challenges in deployment, as many organizations lack integrated technical infrastructure to deploy the model between different departments and business units. These challenges in deployment also include data in different data sources, requirement to integrate the model in to different applications.

Predictive Model Deployment & Monitoring

Predictive Model Deployment & Monitoring

Validation of Predictive Models

Validation of predictive models are generally done for ensuring that predictors used doesn’t have legal issues, and also for the validation of  distributions, analytical algorithms and pre deployment scores.

Deployment of Predictive Models

After the model is validated, the model is moved to production by implementing a scoring system where the model is applied to new data that doesn’t have a dependent variable. For the models which has impact to operational business decisions, such as an application score model or a cross sell model, the implementation system is generally an operational enterprise planning system or a transaction handling system.

Approaches in Deployment

1. Scoring the model : The model is scored and the score value is provided in to business for operational effectiveness which is used in actions and decisions.
2. Integrates with Reporting : The model is integrated with reporting in business intelligence tools and often used as a reference point for collaboration and consultation.
3. Integrates with Application : Model is integrated with applications such as call center and used in the operational business.

Monitoring of Predictive Models

The deployed predictive models are monitored for model performance. Generally the deployed models are repeatedly published in a production environment and the model performance reduces over the period of time. Organizations have process built in to systematically detect the performance reduction in the deployed models to find and obsolete models and to build new ones.

Predictive Model Markup Language

The Predictive Model Markup Language (PMML) is an XML language for statistical and data mining models which makes it easy to move models between different applications and platforms. PMML is the leading standard for predictive analytics models and supported by over 20 vendors and organizations such as IBM,SAS,SAP etc.

Functionalities in Software

1. Create, delete, merge models
2. Extract and import models in formats such as spar file and PMML format.

1.Predictive Analytics Software

SAS Predictive Analytics, IBM Predictive Analytics, SAP Predictive Analytics, RapidMiner, Angoss Predictive Analytics, GraphLab Create, SAP InfiniteInsight, FICO Predictive Analytics, Salford Analytics, Oracle Data Mining (ODM), TIMi Suite, TIBCO Analytics, Alteryx Analytics, Alpine Chorus, KNIME, Actian Analytics Platform, Portrait, Predixion, Data Science Studio, H2O, Analytics Solver, STATISTICA, Viscovery Data Mining Suite, Lavastorm Analytics Engine, Rapid Insight Analytics, Advanced Miner, CMSR Data Miner Suite, GMDH Shell, Mathematica, MATLAB, and Minitab are some of the vendors of proprietary predictive analytics solutions in no particular order.

Click on the button below for a review of the top predictive analytics proprietary software solutions.

Top Predictive Analytics proprietary Software

SAP Predictive Analytics

SAP Predictive Analytics

R, Orange, RapidMiner, Weka, GraphLab Create, Octave, Data Science Studio (DSS), H2O, Lavastorm Public Edition, Tanagra, PredictionIO, HP Distributed R, KNIME, scikit-learn, Actian Analytics Platform, Apache Spark MLlib, Apache Mahout, LIBLINEAR, Vowpal Wabbit, NumPy , and SciPy are some of the key players in the freeware predictive analytics market in no particular order. Click on the button below for a review of the top predictive analytics freeware software solutions.

Predictive Analytics Freeware Software


More Information on Predictive Analysis Process

Predictive Analytics Process Flow

Predictive Analytics Process Flow

For more information of predictive analytics process, please review the overview of each components in the predictive analytics process: data collection (data mining), data analysis, statistical analysis, predictive modeling and predictive model deployment.

Predictive Analytics Software

You may also like to review the predictive analytics free software list :
Predictive Analytics Freeware Software

You may also like to review the predictive analytics software API :
Predictive Analytics Software API

You may also like to review the top predictive analytics proprietary software list:
Top Predictive Analytics proprietary Software


What's your reaction?
Love It
Very Good
About The Author