Models List
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-09.)
Models List has 18 facts recorded in Dontopedia across 4 references, with 2 live disagreements.
Mostly:contains(8), contains model(5), rdf:type(2)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (11)
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.
iteratesOverIterates Over(2)
- Iteration Structure
ex:iteration-structure - Model Evaluation
ex:model-evaluation
providesProvides(2)
- Hermes Models Endpoint
ex:hermes-models-endpoint - Qwen Models Endpoint
ex:qwen-models-endpoint
comparesModelsCompares Models(1)
- Model Training Stage
ex:model-training-stage
describesDescribes(1)
- Comment Models
ex:comment-models
hostsRegisteredModelsHosts Registered Models(1)
- Evals Blah Dev
ex:evals-blah-dev
listsPartialModelsLists Partial Models(1)
- Models Summary Message
ex:models-summary-message
processesEachModelProcesses Each Model(1)
- Sequential Grid Search
ex:sequential-grid-search
returnsModelsListReturns Models List(1)
- Tpmjs Registry Execute
ex:tpmjs-registry-execute
step3Step3(1)
- Sequential Flow
ex:sequential-flow
Other facts (18)
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.
| Predicate | Value | Ref |
|---|---|---|
| Contains | Logistic Regression Model | [2] |
| Contains | Random Forest Model | [2] |
| Contains | Gradient Boosting Model | [2] |
| Contains | Svm Model | [2] |
| Contains | Decision Tree Model | [2] |
| Contains | Naive Bayes Model | [2] |
| Contains | Logistic Regression | [4] |
| Contains | Naive Bayes | [4] |
| Contains Model | Logistic Regression Model | [3] |
| Contains Model | Naive Bayes Model | [3] |
| Contains Model | Decision Tree Model | [3] |
| Contains Model | Linear Svm Model | [3] |
| Contains Model | Lightgbm Model | [3] |
| Rdf:type | Model Collection | [2] |
| Rdf:type | Model Collection | [3] |
| Is Truncated | True | [1] |
| Contains More Than Listed | True | [1] |
| Has Element Type | Model Tuple | [2] |
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 (4)
ctx:discord/blah/omega/part-1150ctx:claims/beam/0daa7c15-b2c7-44ef-a5e9-390bf6864c0a- full textbeam-chunktext/plain1 KB
doc:beam/0daa7c15-b2c7-44ef-a5e9-390bf6864c0aShow excerpt
df = pd.read_csv('data.csv') # Split the data into training and testing sets X_train, X_test, y_train, y_test = train_test_split(df['text'], df['label'], test_size=0.2, random_state=_42) # Feature extraction vectorizer = TfidfVectorizer()…
ctx:claims/beam/b3aa5dac-a3f5-477c-922c-cef12e6cc5a9- full textbeam-chunktext/plain1 KB
doc:beam/b3aa5dac-a3f5-477c-922c-cef12e6cc5a9Show excerpt
X_train, X_test, y_train, y_test = train_test_split(df['text'], df['label'], test_size=0.2, random_state=42) # Feature extraction vectorizer = TfidfVectorizer() X_train_tfidf = vectorizer.fit_transform(X_train) X_test_tfidf = vectorizer.tr…
ctx:claims/beam/7835e578-f2e3-46a0-aa40-4497812bf8de- full textbeam-chunktext/plain1 KB
doc:beam/7835e578-f2e3-46a0-aa40-4497812bf8deShow excerpt
recall = recall_score(y_test, predictions) print(f'{name} Recall score: {recall:.3f}') print(classification_report(y_test, predictions)) print(confusion_matrix(y_test, predictions)) print('-' * 50) ``` ### Explanat…
See also
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