Training and Testing Sets
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Training and Testing Sets has 5 facts recorded in Dontopedia across 2 references, with 1 live disagreement.
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splitsDataSplits Data(2)
- Code Example
ex:code-example - Train Test Split
ex:train-test-split
splitsDatasetSplits Dataset(1)
- Train Test Split
ex:train-test-split
Other facts (5)
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 |
|---|---|---|
| Components | Train Text | [2] |
| Components | Test Text | [2] |
| Components | Train Labels | [2] |
| Components | Test Labels | [2] |
| Rdf:type | Dataset Partition | [1] |
Timeline
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References (2)
ctx:claims/beam/ba4ebe5f-d07c-449d-a419-da14a14caa93- full textbeam-chunktext/plain1 KB
doc:beam/ba4ebe5f-d07c-449d-a419-da14a14caa93Show excerpt
from sklearn.model_selection import train_test_split from sklearn.ensemble import RandomForestClassifier from sklearn.metrics import accuracy_score # Load dataset and split into training and testing sets X_train, X_test, y_train, y_test = …
ctx:claims/beam/82845305-f1a5-445b-8904-5422354c0e4f- full textbeam-chunktext/plain1 KB
doc:beam/82845305-f1a5-445b-8904-5422354c0e4fShow excerpt
[Turn 10574] User: I'm running a POC to test spelling correction on 1,200 inputs, and I'm achieving 90% accuracy rate. However, I'm not sure how to optimize my model for better performance. Can you help me explore different algorithms and t…
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