SAS JMP Pro 17.1 Multilingual macOS
Languages: Multilingual | File Size: 1.4 GB
Extend the value of JMP to solve bigger and more challenging analytic problems with the latest data science techniques, including predictive modeling and machine learning.
Build better modelsWithout the right predictive analytics tools, building a model to predict what will happen with new customers, new processes or new risks becomes much more difficult. JMP Pro offers a rich set of algorithms that lets you build better models.
JMP PRO predictive modelsEnhance the power of your predictive models with various types of data, including unstructured text data you've collected - repair logs, engineering reports, customer survey response comments and more. Use JMP Pro to organize and transform data into usable additions to your predictive models, enabling more confident decision making.
JMP PRO central modelingHandling your models doesn't have to be painful - JMP Pro makes it easy to find the best fit to your data with model screening. Easily build candidate models then profile, compare and generate score code in C, Python, JavaScript, SAS or SQL.
Predictive Modeling and Cross-ValidationUse the JMP Pro set of rich algorithms to build and validate your models more effectively.
Model Screening and ComparisonBuild a variety of models and determine the best for the problem you are trying to solve.
Formula Depot and Score CodeOrganize your models and save model score code in SAS, C, Python, Javascript, SQL.
Structural Equation Modeling (SEM)Framework to fit a variety of models, including confirmatory factor analysis, path models, measurement error models, and latent growth curve models.
Modern ModelingUse new modeling techniques, including Generalized Regression with penalized methods, to build better models, even with challenging data.
Functional Data AnalysisCreate models of data that are functions, signals or series with Functional Data Explorer (FDE).
Reliability Block DiagramsEasily fix weak spots in your system and be better informed to prevent future system failures.
Repairable Systems SimulationSimulate system repair events to understand downtime and number and cost of repairable events.
Covering ArraysDesign your experiment to maximize the probability of finding defects while minimizing cost and time.
Term Selection and Sentiment AnalysisUse your unstructured data to identify terms associated with a response and explore basic sentiment.
Mixed ModelsAnalyze data involving both time and space, where multiple subjects are measured or groups of variables are correlated.
Uplift ModelsPredict consumer segments most likely to respond favorably to an action, allowing targeted marketing decisions.
Advanced Computational StatisticsUse exact statistical tests, exact non-parametric statistical tests and bootstrapping statistics.
Generalized Linear Mixed Models (GLMM)Enables fitting of models with both non-Gaussian response variables and random design effects.
Release Notes
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https://www.jmp.com/content/dam/jmp/documents/en/support/jmp171/release-notes.pdf
System Requirements
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https://www.jmp.com/en_nl/support/system-requirements.html
Homepage:
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https://www.jmp.com/en_gb/software/predictive-analytics-software.html
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