A Closer Look at TinMan Patterns
Import and Spatially Explore Your Data
Import your csv data as rows of patterns or collections of feature values representing sets of circumstances or attributes of any class.
Instantly visualize seperation and grouping within each attribute across classes to determine variance and association.
Easily Perform Matching Tests and Export Results
Determine how many recorded feature vectors for each class are to be used in establishing a registered identity.
Then test and instantly perform matching feature by feature vector by vector to determine strength of configured identity. Export results and group by vector or class.
Apply Analytical Tools to Determine Meaningful Features
Apply weighting and exclusion tests on various features to easily see impact on classification results across feature vectors. Rule out meaningless features and add weight to those that
help distinguish accurate identity. Apply density maps, filters and range blocks to visually reach conclusions.