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https://dev.mysql.com/doc/mysql-ai/9.5/en/mys-ai-aml-model-quality.html
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 dataset. You cannot score a model with a topic ...
https://dev.mysql.com/doc/mysql-ai/9.5/en/mys-ai-aml-models-delete.html
Users that create models or have the required privileges to a model on the MODEL_CATALOG table can delete them. Before You Begin Review how to Create a Machine Learning Model. Delete a Model To delete a model from the model catalog table: Query the ...
https://dev.mysql.com/doc/mysql-ai/9.5/en/mys-ai-aml-onnx-metadata.html
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 of each column to an ONNX model data type. For example, to convert inputs of the type tensor(float) to ...
https://dev.mysql.com/doc/mysql-ai/9.5/en/mys-ai-aml-prepare-an-anomaly-detection-model.html
This topic describes how to prepare the data to use for two anomaly detection machine learning models: a semi-supervised anomaly detection model, and an unsupervised anomaly detection model for logs. To prepare the data for this use case, you set ...
https://dev.mysql.com/doc/mysql-ai/9.5/en/mys-ai-aml-prepare-data-split.html
You can automatically create training and testing datasets with the TRAIN_TEST_SPLIT routine. Overview The TRAIN_TEST_SPLIT routine takes your datasets and prepares new tables for training and testing machine learning models. Two new tables in the ...
https://dev.mysql.com/doc/mysql-ai/9.5/en/mys-ai-aml-regression-train.html
After preparing the data for a regression model, you can train the model. Before You Begin Review and complete all the tasks to Prepare Data for a Regression Model. Training the Model Train the model with the ML_TRAIN routine and use the ...
https://dev.mysql.com/doc/mysql-ai/9.5/en/mys-ai-aml-scoring-a-forecasting-model.html
After generating predictions, you can score the model to assess its reliability. For a list of scoring metrics you can use with forecasting models, see Forecasting Metrics. For this use case, you use the test dataset for validation. In a real-world ...
https://dev.mysql.com/doc/mysql-ai/9.5/en/mys-ai-aml-scoring-a-recommendation-model.html
After generating predicted ratings/rankings and recommendations, you can score the model to assess its reliability. For a list of scoring metrics you can use with recommendation models, see Recommendation Model Metrics. For this use case, you use ...
https://dev.mysql.com/doc/mysql-ai/9.5/en/mys-ai-aml-topic-modeling-train.html
After preparing the data for topic modeling, you can train the model. Before You Begin Review and complete all the tasks to Prepare Data for Topic Modeling. Requirements for Topic Modeling Training Define the following required parameters for topic ...
https://dev.mysql.com/doc/mysql-ai/9.5/en/mys-ai-aml-training-a-forecasting-model.html
After preparing the data for a forecasting model, you can train the model. Before You Begin Requirements for Forecasting Training Forecasting Options Unsupported Routines Training the Model What's Next Before You Begin Review and complete all the ...