iris dataset
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)
iris dataset has 10 facts recorded in Dontopedia across 3 references, with 3 live disagreements.
Mostly:rdf:type(3), has attribute(2), has(2)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (4)
Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.
returnsReturns(2)
- Load Iris
ex:load-iris - Load Iris Function
ex:load-iris-function
assigned-valueAssigned Value(1)
- Iris
ex:iris
createsCreates(1)
- Example Usage
ex:example-usage
Other facts (9)
The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.
Timeline
Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.
References (3)
ctx:claims/beam/7ef0c749-7e6a-4bc4-b3d0-d4b9ba48ae8e- full textbeam-chunktext/plain1 KB
doc:beam/7ef0c749-7e6a-4bc4-b3d0-d4b9ba48ae8eShow excerpt
X_train, X_val = X[train_index], X[val_index] y_train, y_val = y[train_index], y[val_index] # Fit the model on the training data model.fit(X_train, y_train) # Predict on the validati…
ctx:claims/beam/16a732b3-3e07-4ba8-a721-14e165b54a5ectx:claims/beam/2372b8a2-d174-4706-8cb6-61a0fe66ec16- full textbeam-chunktext/plain1 KB
doc:beam/2372b8a2-d174-4706-8cb6-61a0fe66ec16Show excerpt
Choose algorithms that are known to be more memory-efficient. For example, decision trees and random forests are generally more memory-efficient than neural networks. ### 6. Garbage Collection Force garbage collection to free up memory whe…
See also
Keep researching
Missing something or suspicious of what's here? Kick off a research session — a Claude agent will investigate, cite its sources, and file new facts into a dedicated context you can review before accepting into the shared view.