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Glossary
Unsupervised Learning

What is Unsupervised Learning? Unsupervised learning is the process of applying machine learning algorithms to unlabeled data . The outcomes are hidden and previously unknown patterns that may provide new insights. Some common use cases are clustering (e.g. customer segmentation), anomaly...


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
H2O Flow

What is H2O Flow? H2O Flow is an open-source user interface for H2O . It is a web-based interactive environment that allows you to combine code execution, text, mathematics, plots, and rich media in a single document. With H2O Flow, you can capture, rerun, annotate, present,...


Glossary
Classification

What is Classification? In machine learning and statistics, classification is the problem of identifying to which of a set of categories (sub-populations) a new observation belongs, on the basis of a training set of data containing observations (or instances) whose category membership is...


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
Ensemble Learning

What is Ensemble Learning? Ensemble machine learning methods use multiple learning algorithms to obtain better predictive performance than any of the individual learning algorithms. Many of the popular modern machine learning algorithms are actually ensembles. For example, Random Forest and...


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...