---
warning: DO NOT CHANGE THIS MANUALLY, THIS IS GENERATED BY https://github.com/duckdb/community-extensions repository, check README there
title: anofox_ml
excerpt: |
  DuckDB Community Extensions
  Machine learning in SQL - 188 scikit-learn-compatible estimators (trees, boosting, linear models, GLMs, SVMs, kNN, naive Bayes, MLPs, clustering, decomposition, preprocessing, text vectorizers, meta-estimators, conformal prediction), fitted per group with an aggregate and stored as BLOBs, plus metrics, cross-validation, tuning and drift detection.

extension:
  name: anofox_ml
  version: 0.2.0
  description: Machine learning in SQL - 188 scikit-learn-compatible estimators (trees, boosting, linear models, GLMs, SVMs, kNN, naive Bayes, MLPs, clustering, decomposition, preprocessing, text vectorizers, meta-estimators, conformal prediction), fitted per group with an aggregate and stored as BLOBs, plus metrics, cross-validation, tuning and drift detection.
  language: C++
  build: cmake
  license: BSL 1.1
  requires_toolchains: rust
  maintainers:
    - sipemu
repo:
  github: DataZooDE/anofox-ml
  ref: 9523f533425d0e52a69fb2b8a8656adb1e3a19b2
  variegata: 9523f533425d0e52a69fb2b8a8656adb1e3a19b2
docs:
  hello_world: |
    CREATE TABLE train AS
      SELECT (i % 2)::DOUBLE AS y, [i::DOUBLE, (i % 2) * 3.0 + (i % 5) * 0.1] AS x
      FROM range(100) t(i);
    -- fit a model in an aggregate; it is an ordinary BLOB value
    CREATE TABLE models AS
      SELECT ml_fit_agg('RandomForestClassifier', y, x, '{"n_estimators": 50, "seed": 42}') AS model
      FROM train;
    SELECT ml_predict(model, [7.0, 3.2]) AS label,
           ml_predict_proba(model, [7.0, 3.2]) AS proba
    FROM models;
  extended_description: |
    anofox_ml brings the anofox-ml Rust library into SQL. `ml_fit_agg(kind, y, x [, params])` fits any of
    188 estimators (see `ml_estimators()`), one model per `GROUP BY` group in parallel; the result is a
    versioned, compressed BLOB you can keep in a table or Parquet file and use with `ml_predict`,
    `ml_predict_proba`, `ml_transform`, `ml_predict_interval` and the other model functions in any later query.
    It also has metric aggregates, cross-validation splitters, grid / random / halving search
    (`ml_tune_agg`), permutation importance, recursive feature elimination and drift detection.
    Documentation: https://github.com/DataZooDE/anofox-ml

extension_star_count: 3
extension_star_count_pretty: 3
extension_download_count: 51
extension_download_count_pretty: 51
image: '/images/community_extensions/social_preview/preview_community_extension_anofox_ml.png'
layout: community_extension_doc
---
### Compatibility Matrix

This table covers all DuckDB releases that have not reached [end-of-life](https://duckdb.org/release_calendar), including LTS releases, and shows the 2 most recent patch releases of each. Older patch releases are not listed, but the extension may be available for them as well.

<div class="extension_compatibility_table"></div>

| Platform | 1.4.4 | 1.4.5 | 1.5.5 | 1.5.6 | 2.0.0 |
| :--- | :---: | :---: | :---: | :---: | :---: |
| Linux AMD64 | ❌ | ❌ | ❌ | ✅ | ✅ |
| Linux ARM64 | ❌ | ❌ | ❌ | ✅ | ✅ |
| macOS AMD64 | ❌ | ❌ | ❌ | ❌ | ❌ |
| macOS ARM64 | ❌ | ❌ | ❌ | ✅ | ✅ |
| Windows AMD64 | ❌ | ❌ | ❌ | ✅ | ✅ |
| Windows ARM64 | ❌ | ❌ | ❌ | ❌ | ❌ |
| WebAssembly | ❌ | ❌ | ❌ | ✅ | ✅ |

### Installing and Loading
```sql
INSTALL {{ page.extension.name }} FROM community;
LOAD {{ page.extension.name }};
```

{% if page.docs.hello_world %}
### Example
```sql
{{ page.docs.hello_world }}```
{% endif %}

{% if page.docs.extended_description %}
### About {{ page.extension.name }}
{{ page.docs.extended_description }}
{% endif %}
### Added Functions

<div class="extension_functions_table"></div>

|         function_name         | function_type | description | comment | examples |
|-------------------------------|---------------|-------------|---------|----------|
| ml_accuracy                   | aggregate     | NULL        | NULL    |          |
| ml_adjusted_rand              | aggregate     | NULL        | NULL    |          |
| ml_average_precision          | aggregate     | NULL        | NULL    |          |
| ml_balanced_accuracy          | aggregate     | NULL        | NULL    |          |
| ml_brier_score                | aggregate     | NULL        | NULL    |          |
| ml_cluster_agg                | aggregate     | NULL        | NULL    |          |
| ml_cluster_by                 | table_macro   | NULL        | NULL    |          |
| ml_cluster_centers            | scalar        | NULL        | NULL    |          |
| ml_coefficients               | scalar        | NULL        | NULL    |          |
| ml_cohen_kappa                | aggregate     | NULL        | NULL    |          |
| ml_conformal_margin           | aggregate     | NULL        | NULL    |          |
| ml_conformalize_agg           | aggregate     | NULL        | NULL    |          |
| ml_covariance                 | scalar        | NULL        | NULL    |          |
| ml_covariance_agg             | aggregate     | NULL        | NULL    |          |
| ml_coverage                   | aggregate     | NULL        | NULL    |          |
| ml_cross_val_predict_by       | table_macro   | NULL        | NULL    |          |
| ml_cv_splits_agg              | aggregate     | NULL        | NULL    |          |
| ml_decision_function          | scalar        | NULL        | NULL    |          |
| ml_dle_estimate_by            | table_macro   | NULL        | NULL    |          |
| ml_domain_classifier_drift_by | table_macro   | NULL        | NULL    |          |
| ml_estimate_bandwidth_agg     | aggregate     | NULL        | NULL    |          |
| ml_estimators                 | table         | NULL        | NULL    |          |
| ml_explained_variance         | aggregate     | NULL        | NULL    |          |
| ml_explained_variance_ratio   | scalar        | NULL        | NULL    |          |
| ml_f1                         | aggregate     | NULL        | NULL    |          |
| ml_fbeta                      | aggregate     | NULL        | NULL    |          |
| ml_feature_importances        | scalar        | NULL        | NULL    |          |
| ml_fit_agg                    | aggregate     | NULL        | NULL    |          |
| ml_fit_predict_by             | table_macro   | NULL        | NULL    |          |
| ml_fit_predict_proba_by       | table_macro   | NULL        | NULL    |          |
| ml_fit_transform_agg          | aggregate     | NULL        | NULL    |          |
| ml_fit_transform_by           | table_macro   | NULL        | NULL    |          |
| ml_fit_with_offset_agg        | aggregate     | NULL        | NULL    |          |
| ml_fit_with_validation_agg    | aggregate     | NULL        | NULL    |          |
| ml_hashing_vectorize          | scalar        | NULL        | NULL    |          |
| ml_hashing_vectorize_sparse   | scalar        | NULL        | NULL    |          |
| ml_interval_score             | aggregate     | NULL        | NULL    |          |
| ml_inverse_transform          | scalar        | NULL        | NULL    |          |
| ml_kneighbors                 | scalar        | NULL        | NULL    |          |
| ml_log_loss                   | aggregate     | NULL        | NULL    |          |
| ml_mae                        | aggregate     | NULL        | NULL    |          |
| ml_mahalanobis                | macro         | NULL        | NULL    |          |
| ml_mape                       | aggregate     | NULL        | NULL    |          |
| ml_matthews_corrcoef          | aggregate     | NULL        | NULL    |          |
| ml_max_error                  | aggregate     | NULL        | NULL    |          |
| ml_mean_pinball_loss          | aggregate     | NULL        | NULL    |          |
| ml_mean_set_size              | macro         | NULL        | NULL    |          |
| ml_mean_squared_log_error     | aggregate     | NULL        | NULL    |          |
| ml_median_absolute_error      | aggregate     | NULL        | NULL    |          |
| ml_model_fitted               | scalar        | NULL        | NULL    |          |
| ml_model_info                 | scalar        | NULL        | NULL    |          |
| ml_model_kind                 | scalar        | NULL        | NULL    |          |
| ml_mse                        | aggregate     | NULL        | NULL    |          |
| ml_multiple_impute_agg        | aggregate     | NULL        | NULL    |          |
| ml_mutual_info_agg            | aggregate     | NULL        | NULL    |          |
| ml_normalized_mutual_info     | aggregate     | NULL        | NULL    |          |
| ml_outlier_score_agg          | aggregate     | NULL        | NULL    |          |
| ml_outlier_score_by           | table_macro   | NULL        | NULL    |          |
| ml_partial_fit_agg            | aggregate     | NULL        | NULL    |          |
| ml_permutation_importance_agg | aggregate     | NULL        | NULL    |          |
| ml_precision                  | aggregate     | NULL        | NULL    |          |
| ml_predict                    | scalar        | NULL        | NULL    |          |
| ml_predict_interval           | scalar        | NULL        | NULL    |          |
| ml_predict_label              | scalar        | NULL        | NULL    |          |
| ml_predict_log_proba          | scalar        | NULL        | NULL    |          |
| ml_predict_proba              | scalar        | NULL        | NULL    |          |
| ml_predict_set                | scalar        | NULL        | NULL    |          |
| ml_predict_std                | scalar        | NULL        | NULL    |          |
| ml_predict_targets            | scalar        | NULL        | NULL    |          |
| ml_purged_cv_splits_agg       | aggregate     | NULL        | NULL    |          |
| ml_r2                         | aggregate     | NULL        | NULL    |          |
| ml_recall                     | aggregate     | NULL        | NULL    |          |
| ml_rfe_agg                    | aggregate     | NULL        | NULL    |          |
| ml_rmse                       | aggregate     | NULL        | NULL    |          |
| ml_roc_auc                    | aggregate     | NULL        | NULL    |          |
| ml_score_samples              | scalar        | NULL        | NULL    |          |
| ml_set_coverage               | macro         | NULL        | NULL    |          |
| ml_silhouette                 | aggregate     | NULL        | NULL    |          |
| ml_spatial_cv_splits_agg      | aggregate     | NULL        | NULL    |          |
| ml_spectral_embedding_agg     | aggregate     | NULL        | NULL    |          |
| ml_staged_predict             | scalar        | NULL        | NULL    |          |
| ml_transform                  | scalar        | NULL        | NULL    |          |
| ml_transform_y                | scalar        | NULL        | NULL    |          |
| ml_tune_agg                   | aggregate     | NULL        | NULL    |          |
| ml_version                    | scalar        | NULL        | NULL    |          |
| ml_warm_start_agg             | aggregate     | NULL        | NULL    |          |

### Overloaded Functions

<div class="extension_functions_table"></div>

This extension does not add any function overloads.

### Added Types

<div class="extension_types_table"></div>

This extension does not add any types.

### Added Settings

<div class="extension_settings_table"></div>

|           name           |                                               description                                                | input_type | scope  | aliases |                   typed_value                   |
|--------------------------|----------------------------------------------------------------------------------------------------------|------------|--------|---------|-------------------------------------------------|
| anofox_ml_max_fit_values | Largest training set (rows x features) one fitting aggregate may hold in memory per group; 0 = unlimited | UBIGINT    | GLOBAL | []      | 100000000                                       |
| anofox_ml_threads        | Threads a single fit may use (forests, ensembles, ...); 0 = DuckDB's threads, 1 = sequential             | UBIGINT    | GLOBAL | []      | 0                                               |
| anofox_telemetry_enabled | Enable or disable anonymous usage telemetry                                                              | BOOLEAN    | GLOBAL | []      | true                                            |
| anofox_telemetry_key     | PostHog API key for telemetry                                                                            | VARCHAR    | GLOBAL | []      | phc_t3wwRLtpyEmLHYaZCSszG0MqVr74J6wnCrj9D41zk2t |
| temp_directory           | Set the directory to which temporary files are written.                                                  | VARCHAR    | GLOBAL | []      | post.db.tmp                                     |