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MySQL Shell 9.4 :: 8.8.2 Restoring a Cluster from Quorum Loss
https://dev.mysql.com/doc/mysql-shell/9.4/en/restore-cluster-from-quorum-loss.html
Important This operation is potentially dangerous because it can create a split-brain scenario if incorrectly used and should be considered a last resort. If an instance (or instances) fail, then a cluster can lose its quorum, which is the ability ...
MySQL Shell 9.4 :: 6.3 Retrieving a Handler Object
https://dev.mysql.com/doc/mysql-shell/9.4/en/retrieving-a-handler.html
For example, when you create a cluster using dba.createCluster(), the operation returns a Cluster object which can be assigned to a variable. When you are working with AdminAPI, you use a handler object which represents the InnoDB Cluster, InnoDB ...
MySQL AI :: Chapter 4 Training and Using Machine Learning Models
https://dev.mysql.com/doc/mysql-ai/9.4/en/myai-ml-machine-learning.html
This chapter describes how to create and manage machine learning models with the AutoML feature of MySQL AI.
MySQL AI :: 4.6.4 Detect Anomalies
https://dev.mysql.com/doc/mysql-ai/9.4/en/mys-ai-aml-anomaly-detection.html
To generate your own datasets to create machine learning models in MySQL AI, learn how to Generate Text-Based Content. Anomaly detection, which is also known as outlier detection, is the machine learning task that finds unusual patterns in data.
MySQL AI :: 4.6.1 Classify Data
https://dev.mysql.com/doc/mysql-ai/9.4/en/mys-ai-aml-classification.html
To generate your own datasets for creating machine learning models in MySQL AI, learn how to Generate Text-Based Content. Classification models predict the discrete value of input data to specific predefined categories. Some examples of ...
MySQL AI :: 4.5.6.1 Generating Prediction Explanations for a Row of Data
https://dev.mysql.com/doc/mysql-ai/9.4/en/mys-ai-aml-explanations-ml-explain-row.html
mysql> SELECT sys.ML_EXPLAIN_ROW(input_data, model_handle, [options]); In the following example, include the session variable previously created. ML_EXPLAIN_ROW explains predictions for one or more rows of unlabeled data. The following example ...
MySQL AI :: 4.5.6.2 Generating Prediction Explanations for a Table
https://dev.mysql.com/doc/mysql-ai/9.4/en/mys-ai-aml-explanations-ml-explain-table.html
ML_EXPLAIN_TABLE explains predictions for an entire table of unlabeled data. We recommend limiting the input table to a maximum of 100 rows. If the input table has more than ten columns, limit it to ten rows. Some of these columns include: ...
MySQL AI :: 4.6.3.1 Forecasting Task Types
https://dev.mysql.com/doc/mysql-ai/9.4/en/mys-ai-aml-forecasting-model-types.html
This topic describes the types of forecasting models supported by AutoML. Univariate Models In a univariate model, you define one numeric column as an endogenous variable, specified as a JSON_ARRAY. For example, you forecast the rainfall for the ...
MySQL AI :: 4.6.3 Generating Forecasts
https://dev.mysql.com/doc/mysql-ai/9.4/en/mys-ai-aml-forecasts.html
To generate your own datasets to create machine learning models in MySQL AI, learn how to Generate Text-Based Content. Some examples of forecasting include predicting the closing price of a stock, predicting the number of units sold in a day, and ...
MySQL AI :: 4.8 Monitoring the Status of AutoML
https://dev.mysql.com/doc/mysql-ai/9.4/en/mys-ai-aml-monitoring.html
See the following to learn more: Managing MySQL Server with systemd A Quick Guide to Using the MySQL Yum Repository What's Next Review Machine Learning Use Cases to create machine learning models with sample datasets. You can monitor the status of ...
Displaying 3551 to 3560 of 3567 total results