Ë
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Wñúh¾l ã óÔ d Z ddlZddlZddlmZ ddlmZmZmZm Z ddl
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Z ddl Z ddlmZmZmZmZmZmZmZmZmZmZmZmZmZ ddl m Z G d de« Z G d d
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« Z G d d e « Z y) zªHeatWave ML model utilities for MySQL Connector/Python.
|
|
Provides classes to manage training, prediction, scoring, and explanations
|
via MySQL HeatWave stored procedures.
|
é N)ÚEnum)ÚAnyÚDictÚOptionalÚUnion) ÚVAR_NAME_SPACEÚatomic_transactionÚ convert_to_dfÚ execute_sqlÚformat_value_sqlÚget_random_nameÚ source_schemaÚsql_response_to_dfÚsql_table_from_dfÚsql_table_to_dfÚ table_existsÚtemporary_sql_tablesÚ validate_name)ÚMySQLConnectionAbstractc óP e Zd ZdZdZdZdZdZdZdZ dZ
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e d e e d f d
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e fd « Zy ) ÚML_TASKz/Enumeration of supported ML tasks for HeatWave.ÚclassificationÚ
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regressionÚ forecastingÚanomaly_detectionÚlog_anomaly_detectionÚrecommendationÚtopic_modelingÚtaskÚreturnc ó> t | t « r| S | j S )a'
|
Return the string representation of a machine learning task.
|
|
Args:
|
task (Union[str, ML_TASK]): The task to convert.
|
Accepts either a task enum member (ML_TASK) or a string.
|
|
Returns:
|
str: The string value of the ML task.
|
)Ú
|
isinstanceÚstrÚvalue)r s úDH:\Change_password\venv_build\Lib\site-packages\mysql/ai/ml/model.pyÚget_task_stringzML_TASK.get_task_stringG s ô dCÔ ØKàzzÐó N)Ú__name__Ú
|
__module__Ú __qualname__Ú__doc__ÚCLASSIFICATIONÚ
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REGRESSIONÚ FORECASTINGÚANOMALY_DETECTIONÚLOG_ANOMALY_DETECTIONÚRECOMMENDATIONÚTOPIC_MODELINGÚ staticmethodr r# r& © r' r% r r < sS Ù9à%NØ JØ KØ+ÐØ 3ÐØ%NØ%Nàðe C¨ NÑ 3ð ¸ò ó ñr' r c
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óH e Zd ZdZej
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dfdedeeef de e fdZ
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de fdZ dede e fd Zde e fd
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Zdede fd Zdd Zdefd Zde fdZdede e de e ddfdZdedede e ddfdZdededede e def
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dZdedede e dej2 fdZy)Ú_MyModelCommona8
|
Common utilities and workflow for MySQL HeatWave ML models.
|
|
This class handles model lifecycle steps such as loading, fitting, scoring,
|
making predictions, and explaining models or predictions. Not intended for
|
direct instantiation, but as a superclass for heatwave model wrappers.
|
|
Attributes:
|
db_connection: MySQL connector database connection.
|
task: ML task, e.g., "classification" or "regression".
|
model_name: Identifier of model in MySQL.
|
schema_name: Database schema used for operations and temp tables.
|
NÚ db_connectionr Ú
|
model_namec óú || _ t j |« | _ t |« | _ t | j « 5 }t |d« ddd« |t | j « }t d| | _ | j d| _ || _ t |« t | j « 5 }t |d| j d|f¬« ddd« y# 1 sw Y xY w# 1 sw Y yxY w)a»
|
Instantiate _MyMLModelCommon.
|
|
References:
|
https://dev.mysql.com/doc/heatwave/en/mys-hwaml-ml-train.html
|
A full list of supported tasks can be found under "Common ML_TRAIN Options"
|
|
Args:
|
db_connection: MySQL database connection.
|
task: ML task type (default: "classification").
|
model_name: Name to register the model within MySQL (default: None).
|
|
Raises:
|
ValueError: If the schema name is not valid
|
DatabaseError:
|
If a database connection issue occurs.
|
If an operational error occurs during execution.
|
|
Returns:
|
None
|
z(CALL sys.ML_CREATE_OR_UPGRADE_CATALOG();Nú.z.scorezSET @z = %s;©Úparams)r7 r r& r r Ú schema_namer r r Ú_is_model_name_availabler Ú model_varÚmodel_var_scorer8 r )Úselfr7 r r8 Úcursors r% Ú__init__z_MyModelCommon.__init__i sø ð6 +ÔÜ×+Ñ+¨DÓ1 Ü(¨ Ó7Ôä × 2Ñ 2Ó 3ð L°vÜ Ð JÔ K÷ Lð Ð Ü(¨×)FÑ)FÓGJä *Ð+¨1¨Z¨LÐ9Ø"&§.¡.Ð!1°Ð 8Ô à$ÜjÔ!ä × 2Ñ 2Ó 3ð V°vÜ %¨¯©Ð'7°vÐ >È
|
À}Õ U÷ Vð V÷ Lð Lú÷ Vð Vús Á C%Â> C1Ã%C.Ã1C:r c óÞ | j « }d| d}d| d| j }t | j « 5 }t ||« |j
|
dkD cddd« S # 1 sw Y yxY w)a%
|
Deletes the model from the model catalog if present
|
|
Raises:
|
DatabaseError:
|
If a database connection issue occurs.
|
If an operational error occurs during execution.
|
|
Returns:
|
Whether the model was deleted
|
Ú
|
ML_SCHEMA_ú.MODEL_CATALOGz DELETE FROM ú WHERE model_handle = @r N)Ú _get_userr? r r7 r Úrowcount)rA Ú current_userÚqualified_model_catalogÚ delete_modelrB s r% Ú _delete_modelz _MyModelCommon._delete_model s~ ð ~~Ó' à$.¨|¨n¸NÐ"KÐ àÐ2Ð3ð 4%Ø%)§^¡^Ð$4ð 6ð ô
|
× 2Ñ 2Ó 3ð '°vÜ Ô -Ø?? QÑ&÷ '÷ 'ò 'ús ¾A#Á#A,c ó¸ dt dt fd}| j « }d| d}d| d}t | j « 5 }t |||f¬« t |« }|j rd }nS|j d
|
¬ « } t j | « d }
|
|
|
j « D ci c] \ } } | || « }} } |cd d d « S c c} } w # 1 sw Y y xY w) a
|
Retrieves the model info from the model_catalog
|
|
Args:
|
model_var: The model alias to retrieve
|
|
Returns:
|
The model info from the model_catalog (None if the model is not present in the catalog)
|
|
Raises:
|
DatabaseError:
|
If a database connection issue occurs.
|
If an operational error occurs during execution.
|
Úelemr c ó t | t « r t j | « } | S | S # t j $ r Y | S w xY w©N)r" r# ÚjsonÚloadsÚJSONDecodeError)rO s r% Ú process_colz3_MyModelCommon._get_model_info.<locals>.process_col¿ sI Ü$¤Ô$ðÜ :: dÓ+Dð K4Køô ×+Ñ+ò ØØKðús + «AÁArE rF úSELECT * FROM z WHERE model_handle = %sr; NÚrecords)Úorientr ) r rH r r7 r r ÚemptyÚto_jsonrR rS Úitems) rA r8 rU rJ rK Ú model_existsrB Ú model_info_dfÚresultÚunprocessed_resultÚunprocessed_result_jsonÚkeyrO s r% Ú_get_model_infoz _MyModelCommon._get_model_info¯ s ð cð ¤có ð ~~Ó' à$.¨|¨n¸NÐ"KÐ à Ð 4Ð 5Ð5MÐ Nð ô × 2Ñ 2Ó 3ð °vÜ °j°]Õ CÜ .¨vÓ 6Mà ×"Ò"Ø à%2×%:Ñ%:À)Ð%:Ó%LÐ"Ü*.¯*©*Ð5GÓ*HÈÑ*KÐ'ð &=×%BÑ%BÓ%D÷á!Tð TÓ*Ñ*ðñ ð
|
÷ ñ ùó÷ ð ús ÁA'CÂ)C
|
Â<CÃ
|
CÃCc ó8 | j | j « S )a
|
Checks if the model name is available.
|
Model info is present in the catalog only if the model was previously fitted.
|
|
Returns:
|
True if the model name is not part of the model catalog
|
|
Raises:
|
DatabaseError:
|
If a database connection issue occurs.
|
If an operational error occurs during execution.
|
)rb r8 )rA s r% Úget_model_infoz _MyModelCommon.get_model_infoÞ s ð ×#Ñ# D§O¡OÓ4Ð4r' c ó( | j |« du S )a1
|
Checks if the model name is available
|
|
Returns:
|
True if the model name is not part of the model catalog
|
|
Raises:
|
DatabaseError:
|
If a database connection issue occurs.
|
If an operational error occurs during execution.
|
N)rb )rA r8 s r% r> z'_MyModelCommon._is_model_name_availableí s ð ×#Ñ# JÓ/°4Ð7Ð7r' c ó t | j « 5 }d| j d}t ||« ddd« y# 1 sw Y yxY w)a
|
Loads the model specified by `self.model_name` into MySQL.
|
After loading, the model is ready to handle ML operations.
|
|
References:
|
https://dev.mysql.com/doc/heatwave/en/mys-hwaml-ml-model-load.html
|
|
Raises:
|
DatabaseError:
|
If the model is not initialized, i.e., fit or import has not been called
|
If a database connection issue occurs.
|
If an operational error occurs during execution.
|
|
Returns:
|
None
|
zCALL sys.ML_MODEL_LOAD(@z, NULL);N)r r7 r? r )rA rB Úload_model_querys r% Ú _load_modelz_MyModelCommon._load_modelû sH ô" × 2Ñ 2Ó 3ð 2°vØ!9¸$¿.¹.Ð9IÈÐ RÐ Ü Ð 0Ô 1÷ 2÷ 2ñ 2ús <¼Ac óÚ t | j « 5 }|j d« |j « d j d« d }t |« cddd« S # 1 sw Y yxY w)a
|
Fetch the current database user (without host).
|
|
Returns:
|
The username string associated with the connection.
|
|
Raises:
|
DatabaseError:
|
If a database connection issue occurs.
|
If an operational error occurs during execution.
|
ValueError: If the user name includes unsupported characters
|
zSELECT CURRENT_USER()r ú@N)r r7 ÚexecuteÚfetchoneÚsplitr )rA rB rJ s r% rH z_MyModelCommon._get_user s_ ô × 2Ñ 2Ó 3ð /°vØ NNÐ2Ô 3Ø!??Ó,¨QÑ/×5Ñ5°cÓ:¸1Ñ=Lä Ó.÷ /÷ /ò /ús AA!Á!A*c ó | j « t | j « 5 }| j « }d| d}d| d| j }t ||« t |« }|j d cddd« S # 1 sw Y yxY w)a°
|
Get model explanations, such as detailed feature importances.
|
|
Returns:
|
dict: Feature importances and model explainability data.
|
|
References:
|
https://dev.mysql.com/doc/heatwave/en/mys-hwaml-model-explanations.html
|
|
Raises:
|
DatabaseError:
|
If the model is not initialized, i.e., fit or import has not been called
|
If a database connection issue occurs.
|
If an operational error occurs during execution.
|
ValueError:
|
If the model does not exist in the model catalog.
|
Should only occur if model was not fitted or was deleted.
|
rE rF z SELECT model_explanation FROM rG ©r r N)rh r r7 rH r? r r Úiloc)rA rB rJ rK Ú explain_queryÚdfs r% Ú explain_modelz _MyModelCommon.explain_model# s ð& ×ÑÔÜ × 2Ñ 2Ó 3ð !°vØ >>Ó+Là(2°<°.ÀÐ&OÐ #à0Ð1HÐ0Ið J)Ø)-¯ © Ð(8ð:ð ô
|
Ô .Ü# FÓ+Bà774=÷ !÷ !ò !ús ¦AA>Á>BÚ
|
table_nameÚtarget_column_nameÚoptionsc ó t |« |t |« d| d}nd}|i }t j |« }| j |d< | j « t | j « 5 }t |« \ }}t |d| j d| d| d| d | j d
|
|¬ « ddd« y# 1 sw Y yxY w) a2
|
Fit an ML model using a referenced SQL table and target column.
|
|
References:
|
https://dev.mysql.com/doc/heatwave/en/mys-hwaml-ml-train.html
|
A full list of supported options can be found under "Common ML_TRAIN Options"
|
|
Args:
|
table_name: Name of the training data table.
|
target_column_name: Name of the target/label column.
|
options: Additional fit/config options (may override defaults).
|
|
Raises:
|
DatabaseError:
|
If provided options are invalid or unsupported.
|
If a database connection issue occurs.
|
If an operational error occurs during execution.
|
ValueError: If the table or target_column name is not valid
|
|
Returns:
|
None
|
Nú'ÚNULLr zCALL sys.ML_TRAIN('r: ú', ú, z, @ú)r; ) r ÚcopyÚdeepcopyr rM r r7 r r r= r? )rA rt ru rv Útarget_col_stringrB Ú placeholdersÚ
|
parameterss r% Ú_fitz_MyModelCommon._fitE sä ô8 jÔ!Ø Ð )Ü Ð,Ô -Ø"#Ð$6Ð#7°qÐ 9Ñ à &Ð à ?ØGÜ-- Ó(Ø ))à ×ÑÔ ä × 2Ñ 2Ó 3ð °vÜ'7¸Ó'@Ñ $L*Ü ØðØ ×(Ñ(Ð)¨¨:¨,°cØ(Ð)¨Ø#nð %Ø Ð'Øð ð "õ ÷ ÷ ñ ús Á/AB9Â9CÚoutput_table_namec ó> t |« t |« | j « t | j « 5 }t |« \ }}t |d| j d| d| j d| j d| d| d |¬« ddd« y# 1 sw Y yxY w) aª
|
Predict on a given data table and write results to an output table.
|
|
References:
|
https://dev.mysql.com/doc/heatwave/en/mys-hwaml-ml-predict-table.html
|
A full list of supported options can be found under "ML_PREDICT_TABLE Options"
|
|
Args:
|
table_name: Name of the SQL table with input data.
|
output_table_name: Name for the SQL output table to contain predictions.
|
options: Optional prediction options.
|
|
Returns:
|
None
|
|
Raises:
|
DatabaseError:
|
If provided options are invalid or unsupported,
|
or if the model is not initialized, i.e., fit or import has not
|
been called
|
If a database connection issue occurs.
|
If an operational error occurs during execution.
|
ValueError: If the table or output_table name is not valid
|
zCALL sys.ML_PREDICT_TABLE('r: ú', @ú, 'rz r| r; N)r rh r r7 r r r= r? )rA rt r rv rB r r s r% Ú_predictz_MyModelCommon._predict~ s³ ô6 jÔ!ÜÐ'Ô(à ×ÑÔÜ × 2Ñ 2Ó 3ð °vÜ'7¸Ó'@Ñ $L*Ü ØðØ ×(Ñ(Ð)¨¨:¨,ð 7Ø Ð'ð (Ø ×(Ñ(Ð)¨Ð+<Ð*=¸SØ#nØð ð "õ ÷ ÷ ñ ús ¼ABÂB Úmetricc óÀ t |« t |« t |« | j « t | j « 5 }t |« \ }}t |d| j d| d| d| j d| j d| d |g|¢¬« t |d | j « t |« }|j d
|
cd d d « S # 1 sw Y y xY w) aI
|
Evaluate model performance with a scoring metric.
|
|
References:
|
https://dev.mysql.com/doc/heatwave/en/mys-hwaml-ml-score.html
|
A full list of supported options can be found under
|
"Options for Recommendation Models" and
|
"Options for Anomaly Detection Models"
|
|
Args:
|
table_name: Table with features and ground truth.
|
target_column_name: Column of true target labels.
|
metric: String name of the metric to compute.
|
options: Optional dictionary of further scoring options.
|
|
Returns:
|
float: Computed score from the ML system.
|
|
Raises:
|
DatabaseError:
|
If provided options are invalid or unsupported,
|
or if the model is not initialized, i.e., fit or import has not
|
been called
|
If a database connection issue occurs.
|
If an operational error occurs during execution.
|
ValueError: If the table or target_column name or metric is not valid
|
zCALL sys.ML_SCORE('r: z', 'r
z, %s, @r{ r| r; zSELECT @ro N) r rh r r7 r r r= r? r@ r rp ) rA rt ru r rv rB r r rr s r% Ú_scorez_MyModelCommon._score¬ sö ôD jÔ!ÜÐ(Ô)ÜfÔ à ×ÑÔÜ × 2Ñ 2Ó 3ð !°vÜ'7¸Ó'@Ñ $L*Ü ØðØ ×(Ñ(Ð)¨¨:¨,ð 7Ø*Ð+ð ,Ø Ð'ð (à ×,Ñ,Ð-¨RØ#nØðð Ð, Ð,õ ô (¨4×+?Ñ+?Ð*@Ð AÔ BÜ# FÓ+Bà774=÷' !÷ !ò !ús ÁBCÃC c ó t |« t |« |ddi}| j « t | j « 5 }t |« \ }}t |d| j d| d| j d| j d| d| d |¬
|
« t |d | j d| « t |« }|cddd« S # 1 sw Y yxY w) a
|
Produce explanations for model predictions on provided data.
|
|
References:
|
https://dev.mysql.com/doc/heatwave/en/mys-hwaml-ml-explain-table.html
|
A full list of supported options can be found under "ML_EXPLAIN_TABLE Options"
|
|
Args:
|
table_name: Name of the SQL table with input data.
|
output_table_name: Name for the SQL table to store explanations.
|
options: Optional dictionary (default:
|
{"prediction_explainer": "permutation_importance"}).
|
|
Returns:
|
DataFrame: Prediction explanations from the output SQL table.
|
|
Raises:
|
DatabaseError:
|
If provided options are invalid or unsupported,
|
or if the model is not initialized, i.e., fit or import has not
|
been called
|
If a database connection issue occurs.
|
If an operational error occurs during execution.
|
ValueError: If the table or output_table name is not valid
|
NÚprediction_explainerÚpermutation_importancezCALL sys.ML_EXPLAIN_TABLE('r: r
r rz r| r; rV ) r rh r r7 r r r= r? r )rA rt r rv rB r r rr s r% Ú_explain_predictionsz#_MyModelCommon._explain_predictionsè sò ô8 jÔ!ÜÐ'Ô(à ?Ø-Ð/GÐHGà ×ÑÔä × 2Ñ 2Ó 3ð °vÜ'7¸Ó'@Ñ $L*Ü ØðØ ×(Ñ(Ð)¨¨:¨,ð 7Ø Ð'ð (Ø ×(Ñ(Ð)¨Ð+<Ð*=¸SØ#nØð ð "õ ô .°×1AÑ1AÐ0BÀ!ÐDUÐCVÐ WÔ XÜ# FÓ+Bà÷# ÷ ò ús ÁA6CÃC )r N)r( r) r* r+ r r, r r r# r rC ÚboolrM Údictrb rd r> rh rH rs r r Úfloatr ÚpdÚ DataFramer r4 r' r% r6 r6 Z sr ñ ð" %,×$:Ñ$:Ø$(ñ ,Và.ð,Vð CLÑ!ð,Vð SMó ,Vð\'tó 'ð0-¨#ð -°(¸4±.ó -ð^ 5 ¨¡ó 5ð 8°3ð 8¸4ó 8ó 2ð*/3ó /ð& !tó !ðD7àð7ð % SMð7ð $ ð 7ð
|
|
ó 7ðr,Ø ð,Ø25ð,Ø@HÈÁð,à ó,ð\:!àð:!ð ð:!ð ð :!ð
|
$ ð :!ð
|
ó :!ðx5Ø ð5Ø25ð5Ø@HÈÁð5à ô5r' r6 c óè e Zd ZdZ d deej ej f de eej ej f de e
|
ddfdZ d deej ej f de e
|
dej fdZ d deej ej f deej ej f d e de e
|
def
|
d
|
Z d deej ej f dedej fd Zy) ÚMyModelzó
|
Convenience class for managing the ML workflow using pandas DataFrames.
|
|
Methods convert in-memory DataFrames into temp SQL tables before delegating to the
|
_MyMLModelCommon routines, and automatically clean up temp resources.
|
NÚXÚyrv r c óV t « t |« c}t | j « 5 }t | j « 5 }|mt |t
|
j « r|j d }nt fd« }|j v rt d| d« j « }|||< |}nd}}t || j |« \ } }
|
|j | j |
|
f« | j |
|
||« ddd« ddd« y# 1 sw Y xY w# 1 sw Y yxY w)a´
|
Fit a model using DataFrame inputs.
|
|
If an 'id' column is defined in either dataframe, it will be used as the primary key.
|
|
References:
|
https://dev.mysql.com/doc/heatwave/en/mys-hwaml-ml-train.html
|
A full list of supported options can be found under "Common ML_TRAIN Options"
|
|
Args:
|
X: Features DataFrame.
|
y: (Optional) Target labels DataFrame or Series. If None, only X is used.
|
options: Additional options to pass to training.
|
|
Returns:
|
None
|
|
Raises:
|
DatabaseError:
|
If provided options are invalid or unsupported.
|
If a database connection issue occurs.
|
If an operational error occurs during execution.
|
|
Notes:
|
Combines X and y as necessary. Creates a temporary table in the schema for training,
|
and deletes it afterward.
|
Nr c ó | j vS rQ ©Úcolumns©Únamer s r% ú<lambda>z MyModel.fit.<locals>.<lambda>U s ø T°·±Ð%: r' zTarget column y with name z' already present in feature dataframe X)r
|
r r7 r r" r r r r Ú
|
ValueErrorr} r r= Úappendr ) rA r r rv rB Útemporary_tablesru Ú df_combinedÚfinal_dfÚ_rt s ` r% Úfitz MyModel.fit( s1 ø ôB QÓ ¤ ¨qÓ!11ô t× 1Ñ 1Ó 2ð ?Ø6<Ü ×!3Ñ!3Ó 4ð ?à8Hà}Ü a¤§ ¡ Ô.à)*¯©°1© Ñ&ä)8Û:ó*Ð&ð &¨¯©Ñ2Ü$Ø4Ð5GÐ4Hð I1ð 1óð ð
|
ffh Ø23 Ð .Ñ/Ø&à%)Ð"Ø ä -¨f°d×6FÑ6FÈÓ QMAzØ × #Ñ # T×%5Ñ%5°zÐ$BÔ Cà IIjÐ"4°gÔ >÷; ?÷ ?÷ ?ñ ?ú÷ ?ð ?ús$ ®D ÁB>DÄD ÄD ÄD Ä D(c óB t |« }t j « 5 t j « 5 }t j
|
|« \ }}|j j
|
|f« t fd« }|j j
|
|f« j |||« t j
|
|« }|d j t j « |d< |cddd« cddd« S # 1 sw Y nxY wddd« y# 1 sw Y yxY w)aõ
|
Generate model predictions using DataFrame input.
|
|
If an 'id' column is defined in either dataframe, it will be used as the primary key.
|
|
References:
|
https://dev.mysql.com/doc/heatwave/en/mys-hwaml-ml-predict-table.html
|
A full list of supported options can be found under "ML_PREDICT_TABLE Options"
|
|
Args:
|
X: DataFrame containing prediction features (no labels).
|
options: Additional prediction settings.
|
|
Returns:
|
DataFrame with prediction results as returned by HeatWave.
|
|
Raises:
|
DatabaseError:
|
If provided options are invalid or unsupported,
|
or if the model is not initialized, i.e., fit or import has not
|
been called
|
If a database connection issue occurs.
|
If an operational error occurs during execution.
|
|
Notes:
|
Temporary SQL tables are created and deleted for input/output.
|
c ó4 t j | « S rQ ©r r= ©rt rB rA s r% r z!MyModel.predict.<locals>.<lambda> ó ø ¤|ØD× ,Ñ ,¨jó(ð $ r' Ú
|
ml_resultsN) r
|
r r7 r r r= r r r r ÚmaprR rS ) rA r rv r¡ r¤ rt r Ú predictionsrB s ` @r% ÚpredictzMyModel.predictj s ù ô@ !Ó ô t× 1Ñ 1Ó 2ð Ø6<Ü ×!3Ñ!3Ó 4ð à8Hä -¨f°d×6FÑ6FÈÓ JMAzØ × #Ñ # T×%5Ñ%5°zÐ$BÔ Cä /ôó!Ð ð
|
× #Ñ # T×%5Ñ%5Ð7HÐ$IÔ Jà MM*Ð&7¸Ô AÜ)¨&°$×2BÑ2BÐDUÓVKð )4°LÑ(A×(EÑ(EÄdÇjÁjÓ(QK Ñ %à ÷) ÷ ÷ ó ú÷ ÷ ñ ús# £D¹B4D Ã- DÄ D ÄDÄD r c óÔ t « t |« c}t | j « 5 }t | j « 5 }t fd« }j « }|||< |} t || j | « \ }
|
} |j | j | f« | j | |||« } | cddd« cddd« S # 1 sw Y nxY wddd« y# 1 sw Y yxY w)a
|
Score the model using X/y data and a selected metric.
|
|
If an 'id' column is defined in either dataframe, it will be used as the primary key.
|
|
References:
|
https://dev.mysql.com/doc/heatwave/en/mys-hwaml-ml-score.html
|
A full list of supported options can be found under
|
"Options for Recommendation Models" and
|
"Options for Anomaly Detection Models"
|
|
Args:
|
X: DataFrame of features.
|
y: DataFrame or Series of labels.
|
metric: Metric name (e.g., "balanced_accuracy").
|
options: Optional ml scoring options.
|
|
Raises:
|
DatabaseError:
|
If provided options are invalid or unsupported,
|
or if the model is not initialized, i.e., fit or import has not
|
been called
|
If a database connection issue occurs.
|
If an operational error occurs during execution.
|
|
Returns:
|
float: Computed score.
|
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Explain model predictions using provided data.
|
|
If an 'id' column is defined in either dataframe, it will be used as the primary key.
|
|
References:
|
https://dev.mysql.com/doc/heatwave/en/mys-hwaml-ml-explain-table.html
|
A full list of supported options can be found under
|
"ML_EXPLAIN_TABLE Options"
|
|
Args:
|
X: DataFrame for which predictions should be explained.
|
options: Optional dictionary of explainability options.
|
|
Returns:
|
DataFrame containing explanation details (feature attributions, etc.)
|
|
Raises:
|
DatabaseError:
|
If provided options are invalid or unsupported, or if the model is not initialized,
|
i.e., fit or import has not been called
|
If a database connection issue occurs.
|
If an operational error occurs during execution.
|
|
Notes:
|
Temporary input/output tables are cleaned up after explanation.
|
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