|Rosella Machine Intelligence & Data Mining|
CMSR Machine Learning / Data Miner / Rule Engine Studio
Codingless Coding-free Machine Learning and Powerful Visualization Tools
No coding errors! No debugging! No package dependency errors!
Deploy/Embed Models on (almost) Any System
Scalable High Performance Computing / Super GPU Speedup
CMSR is developed with Java. It runs on Windows as well as MacOS seamlessly. More importantly, it's faster than C/C++-based ML systems because of Java's Just-in-time compiler. It runs upto 2 to 3 times faster than C/C++ systems on Windows.
Computer Vision and Embedded Applications
CMSR Studio can generate computer vision model deployment program source codes for GPU in C++ and Java and Swift and Objective-C for the following GPU API platforms. Note that compute vision models are compute intensive. So GPU deployment is essential.
- OpenCL: Java and C++. Windows, Linux, Android. SBC.
- CUDA: Java and C++. Windows, Linux. SBC.
- OpenGL ES (GLES3): C++. Android, Raspberry Pi. SBC.
- Apple Metal: Swift and Objective-C. MacOS, iOS, iTablet.
- Multiple CPU threads: Java and C++.
Generate source code. Include in your application and call. That's what all it takes! CMSR Computer Viision tasks include;
- Image classification: Given an image, determines the type of image.
- Image regression: Given an image, predicts a single or multiple output values.
- Object detection: Given an image, detect objects as bounding boxes, a la YOLO.
- Similarity regression of two images, e.g., face recognition.
- Stereoscopic regression of two images, e.g., distance estimation.
Models incorporate pre- and post processing as follows;
- Color inversion.
- Color transformation and value encoding.
- Histogram equalization.
- Object filtering and duplicate removal.
All these are automatic upon selecting options. Generated program codes will incorporate these. So no need for extra coding. For more about computer vision on edge computing devices, see the following links;
For an example use of computer vision,
please check Skin cancer checker online app.
Predictive Modeling Algorithms and Applications
- ANN (Artificial Neural Network): Predictive modeling for statistical data. For application examples, read risk management for credit, finance, insurance, etc.
- Decision tree: for classification and drill-down analysis.
- SOM (Self Organizing Maps): Clustering and customer segmentation.
Other Algorithms and Charts
- Rule engine with machine learning models
- Hotspot drill-down analysis
- Association rules - Apriori algorithm
- Co-items shopping basket analysis
- Confusion map analysis
- Correlation analysis
- Time-series (with regression, seasonal adjustment, charts)
- Time-series similarity analysis
- Group-by reports (with regression, seasonal adjustment, charts)
- Cross table reports
- Visual charts: bars, 3D bars, areas, pies, lines, histograms, Sankey diagram, histobars, scatterplots, boxplots, normal quantile plots, ...
- t-tests, ANOVA, ...
- And more ...
For more information, please click here.
For free downloads, please visit CMSR Download Request.
[ 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 / Rule Engine Studio.)