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https://dev.mysql.com/doc/mysql-shell/9.4/en/mysql-shell-reporting-builtin-thread.html
The thread report has a custom output format that includes vertical listings and tables presented in different sections, and you cannot change this output format. Any truncated statements displayed in the report are truncated according to the ...
https://dev.mysql.com/doc/mysql-shell/9.4/en/mysql-shell-reporting-builtin-threads.html
The threads report is of the list type, and by default the results are returned as a table, but you can use the --vertical (or -E) option to display them in vertical format. Any truncated statements displayed in the report are truncated according to ... The built-in MySQL Shell report threads lists the current threads in the connected MySQL server which belong to the user account that is used to run the ...
https://dev.mysql.com/doc/mysql-shell/9.4/en/mysql-shell-utilities-json-mysqlsh.html
options The --collection, --table, and --tableColumn options specify a target collection or a target table and column. With the mysqlsh command interface, you invoke the JSON import utility as follows: mysqlsh user@host:port/mydb -- util importJson ...
https://dev.mysql.com/doc/mysql-ai/9.4/en/mys-ai-aml-automl-privileges.html
Database Privileges You need the following privileges to access the database that stores the input tables (training datasets). mysql> GRANT SELECT, ALTER ON database_name.* TO 'user_name'@'%'; You need the following privileges to access the database ... To use AutoML, ask the admin user to grant you the following ...
https://dev.mysql.com/doc/mysql-ai/9.4/en/mys-ai-aml-classification-train.html
Training the Model Train the model with the ML_TRAIN routine and use the training_data table previously created. mysql> CALL sys.ML_TRAIN('table_name', 'target_column_name', JSON_OBJECT('task', 'task_name'), model_handle); Replace table_name, ...
https://dev.mysql.com/doc/mysql-ai/9.4/en/mys-ai-aml-load-model.html
Query the model handle, model owner, and the trained table name from the model catalog table. You must load a machine learning model from the model catalog before running AutoML routines other than ML_TRAIN. A model remains loaded and can be called ...
https://dev.mysql.com/doc/mysql-ai/9.4/en/mys-ai-aml-model-quality.html
After training and loading the model, prepare a table of labeled data to score that has a different set of data from the trained model. mysql> CALL sys.ML_SCORE(table_name, target_column_name, model_handle, metric, score, [options]); The following ... ML_SCORE scores a model by generating predictions using the feature columns in a labeled dataset as input and comparing the predictions to ground truth values in the target column of the labeled ...
https://dev.mysql.com/doc/mysql-ai/9.4/en/mys-ai-aml-regression-train.html
Training the Model Train the model with the ML_TRAIN routine and use the house_price_training table previously created. mysql> CALL sys.ML_TRAIN('table_name', 'target_column_name', JSON_OBJECT('task', 'task_name'), @variable); Replace table_name, ...
https://dev.mysql.com/doc/mysql-ai/9.4/en/mys-ai-aml-topic-modeling-train.html
Therefore, you cannot use the following options for topic modeling: model_list optimization_metric exclude_model_list exclude_column_list include_column_list Unsupported Routines You cannot run the following routines for topic modeling: ML_EXPLAIN ... After preparing the data for topic modeling, you can train the ...
https://dev.mysql.com/doc/mysql-ai/9.4/en/mys-ai-genai-chat-details.html
Viewing Details To view the chat session details, inspect the @chat_options variable: mysql> SELECT JSON_PRETTY(@chat_options); The output includes the following details about a chat session: Vector store tables: in the database which were ... This ...