Common ML Algorithms

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Across
  1. 1. The variable that a model aims to predict.
  2. 4. Learning type where the model learns from labeled data.
  3. 6. Learning type where the model identifies patterns in unlabeled data.
  4. 11. The process of teaching a model using data.
  5. 13. Metric used to evaluate classification models by measuring correct predictions.
  6. 14. A mathematical representation used to make predictions based on data.
  7. 15. Unsupervised learning task to group similar data points.
Down
  1. 2. Dataset used to evaluate the final performance of a model.
  2. 3. Supervised learning task to predict continuous numeric values.
  3. 5. Popular Python library for machine learning tasks.
  4. 7. Dimensionality reduction technique to reduce data features.
  5. 8. A tree based algorithm used for both classification and regression tasks.
  6. 9. The output of a model when applied to new data.
  7. 10. ...........Matrix to evaluate classification models by showing true and false predictions.
  8. 12. The independent variables used by the model to make predictions.