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Glossary
Model Validation / Hold-Out / Cross-Validation

What is Model Validation? Model validation is a technique to estimate model performance on unseen data. There are two common approaches: hold-out and cross-validation. For hold-out validation, we split the training data into a training and validation set, which is similar to a test set....


Glossary
Automatic Machine Learning (AutoML)

What is Automatic Machine Learning (AutoML)? Choosing the best machine learning models and tuning them can be time consuming and exhaustive. Often, it requires years of expertise to know which parameters to tune. The field of AutoML focuses on solving this issue. AutoML is useful both for...


Glossary
Regression Analysis / Regressor Model

What is Regression? Regression is one of the most common machine learning techniques which estimates a continuous variable based on a list of inputs. There are many types of regression models from simple linear regression to the more advanced gradient boosting machines and neural networks [1...


Glossary
Machine Learning Experiment

What is a Machine Learning Experiment? Machine learning experiment involves importing a data set, training multiple machine learning models to predict one or more labels from that data set and manually evaluating all those models until one finds the most accurate model. H2O...


Glossary
Model Object, Optimized (MOJO)

What is a MOJO? MOJO (stands for Model Object, Optimized) [1] is a standalone, low-latency model object designed to be easily embeddable in production environments. In Driverless AI , the MOJO Model is combined with a feature engineering pipeline to create a MOJO scoring pipeline ...


Glossary
Scoring Pipeline

What is a Scoring Pipeline? In machine learning , pipelines are the automation of sequential steps in a workflow. These steps may include data preparation , model training , validation , packaging , deployment as well as monitoring. A scoring pipeline is usually a part of the deployment...


Glossary
Scoring / Making Predictions / Inferencing

What is Scoring? Scoring, also known as inferencing, is the process of using a trained machine learning model to make predictions based on input data. There are two types of scoring: batch scoring and real-time scoring. Batch scoring involves using the model to make predictions on multiple...


Glossary
Machine Learning Model

What is a Machine Learning Model? A machine learning model is generated by either supervised or unsupervised training. It is an abstract representation of relationships between variables learned from data. Once trained , a machine learning model can be used to make predictions based on...


Glossary
Machine Learning Algorithms

What are Machine Learning Algorithms? Machine learning algorithms can uncover hidden patterns in data or discover relationships between inputs (features) and outputs ( targets ) without explicitly programmed. There are four common types of machine learning algorithms: supervised , ...


Glossary
Machine Learning Model Deployment / Productionization / Productionizing Machine Learning Models

What is Machine Learning Model Deployment? Machine Learning Model Deployment involves making the model available in production environments, so they can be used to make predictions and provide value for other software systems. Both H2O-3 and Driverless AI models can be made available...