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https://dev.mysql.com/doc/relnotes/connector-j/en/news-9-5-0.html
Errors were returned similar to the following: Can not issue executeUpdate() or executeLargeUpdate() with statements that produce result sets (Bug #34464351) Calling the equals method on MultiHostConnectionProxy with a null argument resulted in a ...
https://dev.mysql.com/doc/mysql-ai/9.5/en/mys-ai-aml-ease-of-use.html
For example: CALL sys.ML_TRAIN('heatwaveml_bench.census_train', 'revenue', NULL, @census_model); The ML_TRAIN routine leverages Oracle AutoML technology to automate training of machine learning models. For example, the following call to the ... The ...
https://dev.mysql.com/doc/mysql-ai/9.5/en/mys-ai-aml-onnx-metadata.html
If the task is NULL, do not provide predictions_name or prediction_probabilities_name as this causes an error. To learn more about model metadata in the model catalog, see Model Metadata. ONNX Inputs Info Use the data_types_map to map the data type ...
https://dev.mysql.com/doc/mysql-ai/9.5/en/mys-ai-aml-prepare-a-forecasting-model.html
mysql> CREATE TABLE electricity_demand ( date DATE PRIMARY KEY, demand FLOAT NOT NULL, temperature FLOAT NOT NULL ); Insert the sample data into the table. This topic describes how to prepare the data to use for a forecasting machine learning model. To prepare the data for this use case, you set up a training dataset and a testing ...
https://dev.mysql.com/doc/mysql-ai/9.5/en/mys-ai-aml-supervised-learning.html
The dataset for this type of model must have a column whose only allowed values are 0 (normal), 1, (anomalous), and NULL (unlabeled). All rows in the dataset are used to train the unsupervised component, while the rows with a value different than ...
https://dev.mysql.com/doc/mysql-ai/9.5/en/mys-ai-aml-topic-modeling-train.html
mysql> CALL sys.ML_TRAIN('topic_modeling_data.movies', NULL, JSON_OBJECT('task', 'topic_modeling', 'document_column', 'description'), @model); Where: topic_modeling_data.movies is the fully qualified name of the table that contains the training ...
https://dev.mysql.com/doc/mysql-ai/9.5/en/mys-mysqlai-ml-generate.html
The ML_GENERATE routine uses the specified large language model (LLM) to generate text-based content as a response for the given natural-language query. It can include the following parameters: task: specifies the task expected from the LLM.
https://dev.mysql.com/doc/mysql-ai/9.5/en/mys-mysqlai-ml-rag.html
The ML_RAG routine performs retrieval-augmented generation (RAG) by: Taking a natural-language query. This routine aims to provide detailed, accurate, and contextually relevant answers by augmenting a generative model with information retrieved ...
https://dev.mysql.com/doc/workbench/en/dbdoc-templates-custom.html
In the simplest case, a template consists of two files: a template file, which has a .tpl extension, and a special file info.xml. A third file is optional, which is the preview image file. This preview file provides a thumbnail image illustrating ...
https://dev.mysql.com/doc/workbench/en/wb-admin-export-import-results.html
Note The result set must have a unique row identifier (such as a Primary Key or NOT NULL unique index) as otherwise values cannot be imported because the result set will be read-only. Export or Import data directly from or into the result set. The ...