Minitab's Salford Predictive Modeler (SPM) is a high-precision and fast-forward software package suitable for developing predictive, descriptive, and analytical models. The platform includes powerful new automation and modeling features that are not found in other packages, as well as CART, MARS, TreeNet, Random Forests engines.
Minitab's Salford Predictive Modeler (SPM) is a high-precision and fast-forward software package suitable for developing predictive, descriptive, and analytical models. The platform includes powerful new automation and modeling features that are not found in other packages, as well as CART, MARS, TreeNet, Random Forests engines.
Introduction to SPM Minitab
The software package covers data mining technologies for classification, regression, survival analysis, lost value analysis, data binning, and grouping/segmentation, with algorithms considered essential in sophisticated data science circles.
Minitab SPM automation speeds up the model creation process by driving substantial parts of process analysis refinement exploration.
Key attributes of SPM Minitab
The software package contains more than 70 prepackaged automation scenarios inspired by how leading model analysts structure their work. With tools to alleviate strenuous work, SPM Minitab allows the user to focus on the creative aspects of model development, ensuring greater efficiency.
With improved regression, classification, and logistic regression algorithms, the platform supports huge datasets.
Mechanisms envisaged
CART: This modeling engine is the definitive classification tree that revolutionized the field of advanced analysis and ushered in the current era of data science.
Random Forests: is a modeling tool that harnesses the power of various alternative analyses, randomization strategies, and learning together.
MARS: Ideal for users who prefer results in a similar way to traditional regression when capturing nonlinearities and essential interactions.
TreeNet: is the most flexible and powerful data mining tool, capable of consistently generating extremely accurate models.
System Requirements
Windows
Operating system (64-bit only): Windows 7 SP 1 or later, Windows 8 or 8.1, Windows 10.
RAM: 2 GB.
Processor: Intel Pentium 4 or AMD Athlon Dual Core, with SSE2 technology.
Hard disk space: Minimum of 2 GB of free space available on hard disk.
Linux
Operating system (Only 64 bits): Ubuntu 14.04 or 16.04, CentOS 6.9 or 7.5, RHEL 6.9 or 7.5.
RAM: 2 GB.
Processor: Intel Pentium 4 or AMD Athlon Dual Core, with SSE2 technology.
Hard disk space: Minimum of 2 GB of free space available on hard disk.
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