|Rosella Machine Intelligence & Data Mining|
CMSR Data Miner / Machine Learning / Rule Engine Studio
Ideal for large enterprises: Simple to deploy advanced sophisticated models on Rosella BI Web Server and on Android devices. Very fast! Rosella BI Server can process complex RME-EP deep learning model HTTP/JSON requests over 5,000 times per second on average dual core computers. (Note that performance can vary depending on neural network sizes.)
Designed for developing AI-based business solutions and embedded applications. For Java/Android applications, APIs are available. For details, please check Java/Android API Manual. For non-Java, such as PHP, HTTP-based RPC can be used.
Excellent algorithms and advanced power tools, super fast, big data (up to 2 billion records), easy-to-use GUI interfaces, smooth database incorporation, superb graphics and user experience!
(1) Rule Engine for Machine Learning / Deep Learning / Expert Systems
- RME-EP: Rule Engine with Machine Learning, Deep Learning, Neural Network
- Easy to build "Deep Learning" hierarchically stacked multiple neural network models
- Combines rule engine and machine learning for predictive modeling
- Forward-chaining rule inference engine
- Rules can be written to incorporate predictive models
- Powerful easy-to-learn rule specification language (derived from SQL)
- Easy-to-use Machine Learning Studio that can generate predictive model evaluation rules automatically.
- Can be used as rule-based data transformation tools
- Implement Radial Basis Function (RBF) using SOM and Neural Network models
- Support many regression, time-series and statistical functions
- Randomization rules can be used to create sampling datasets from database tables
- Database scoring: Apply RME-EP models to database records
- Models are deployed on Web and Android
- Want to develop super intelligent models? Start with the example in this page and expand it!
(2) Predictive Modeling by Machine Learning
- Neural Network: ANN Multi-layer Deep Neural Network (Incremental learning with multiple training datasets, network pruning and compression, random data training, best model search, network evolution diagram, GPU JOCL/OpenCL computing support.)
- SOM: Self Organizing Maps for Clustering
- Decision Tree (Cramer, Entrophy, GINI, Chisquare, Expected Accuracy, etc.) (Note that Cramer tends to produce trees with fewer nodes but more accurate than other well-known decision tree algorithms.)
- Rule-based predictive model integration
- Correlation analysis for predictive modeling variable relevancy analysis
- Database scoring: Apply predictive models to database records
- Models are deployed on Web and Android
(3) Clustering and Segmentation: Customer Prioritizing and Targeting
- Neural Clustering (SOM) with Response and Profit Modeling/Analysis
- Decision Tree with Response and Profit Modeling/Analysis
- Database scoring: Apply segmentation models to database records
- For step-by-step guides for customer segmentation, prioritizing and targeting, please read Customer Prioritizing and Segmentation (PDF).
(4) Hotspot Drill-down and Profiling
- Hotspot Drill-down Analysis and Profiling
(5) Cross-sell Shopping Basket Analysis
- Association Rules - Apriori Algorithm (Works with both database and file data. Big data!)
- Co-items Shopping Basket Analysis
(6) Data Mining and Statistics
- Cross tables with deviation/hotspot analysis.
- Groupby tables with trend analysis.
- Power visual charts: 3D bars, bars, histograms, Sankey diagram, histobars, scatterplots, boxplots, and more.
(7) Database Analytics and Tools
- Power visual charts: 3D bars, bars, histograms, histobars, scatterplots, and more.
- Crosstable and group-by reports.
- Database metadata navigation and data browser.
- Data import and export tools.
- SQL query/batch tools.
(8) Special Features
- 64-bit integer and floating point data representation.
- Large in-memory optimized for fast speed (currently up to 2GB).
- Super fast and Big data (single dataset up to 2 billion records and 1 tera-bytes).
- Connect to and update major relational DBMS through JDBC.
- Data Miner optimized for MicroSoft MS SQL Server, MySQL / MariaDB, PostgreSQL, MS Office Access.
- Deploy/publish predictive models on Android phones and Android tablets with MyDataSay app. For downloads, click here.
- Runs on multiple OS: Windows, Linux, Mac OS X / MacOS.
MacOS Data Mining / Machine Learning Software
CMSR Data Miner / Machine Learning Studio is based on Java(TM). It runs on Mac OS X / macOS seamlessly.
[ Screenshots of CMSR Data Miner / Machine Learning Studio ]
(For full view, click the images.)
(Note that StarProbe data miner is replaced with CMSR Data Miner / Machine Learning Studio.)