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What is Salford Predictive Modeler (SPM)?

The Salford Predictive Modeler® (SPM) software suite is renowned for its remarkable speed and accuracy in crafting predictive, descriptive, or analytical models. Featuring engines such as CART®, TreeNet®, and Random Forests®, along with innovative automation capabilities and unique modeling functionalities, SPM stands out in the realm of data analysis tools. This comprehensive suite encompasses a range of data mining technologies, including classification, regression, survival analysis, and methods for handling missing values, as well as data binning and clustering. SPM algorithms are invaluable in sophisticated data science applications, making them a cornerstone for analysts seeking to derive insights from complex datasets. The automation of model construction is significantly streamlined with SPM, facilitating a more efficient exploration and refinement process. Furthermore, the suite allows for the seamless integration of results from various modeling approaches into a single, cohesive package, enhancing the review process for users. This combination of features not only boosts productivity but also empowers data professionals to make informed decisions more effectively.

What is Modeller?

In the current era of machine learning, software designed for model development leverages over three decades of expertise in credit risk modeling. Modeller stands out as a versatile, clear, and interactive tool that empowers organizations to maximize the potential of their analytical teams. It provides a wide range of methodologies, facilitates the swift creation of robust models, ensures comprehensive explanations, and nurtures the growth of junior team members. Users can select from diverse modeling approaches, including machine learning, to attain the highest levels of predictive precision, particularly when dealing with intricate relationships and multicollinearity. With a simple click, one can generate standard industry binary and continuous target models. The software supports decision tree modeling through CHAID trees and CART methods, along with options like logistic regression, elastic net models, survival analysis (Cox PH), random forest, XGBoost, and stochastic gradient descent. Furthermore, it offers export capabilities to SAS, SQL, and PMML, enabling seamless integration with other scoring and decision-making applications. This flexibility ensures that organizations can easily adapt the models to fit their specific operational contexts and requirements.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS
Windows
On-Prem

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Minitab

Date Founded

1972

Company Location

United States

Company Website

www.minitab.com/en-us/products/spm/

Company Facts

Organization Name

Paragon Business Solutions

Date Founded

1991

Company Location

United Kingdom

Company Website

www.credit-scoring.co.uk/modeller

Categories and Features

Data Mining

Predictive Modeling

Machine Learning

Not specified

Predictive Analytics

Not specified

Categories and Features

Credit Management

Not specified

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