Glossary Archives - Page 4 of 10

Gini

Written by Evispot. Posted in g, Glossary.

The Gini coefficient is a well-established method to quantify the inequality among values of a frequency distribution, and can be used to measure the quality of a binary classifier. Gini is measured between 0 and 1. A Gini index of 0 expresses perfect...

ROC curve

Written by Evispot. Posted in Glossary, r.

A receiver operating characteristic (ROC), or simply ROC curve, is a graphical plot which illustrates the performance of a binary classifier system as its discrimination threshold is varied. It is created by plotting the fraction of true positives...

Undersampling

Written by Evispot. Posted in Glossary, u.

It’s the process of balancing a data set by discarding examples of the overrepresented class so that each has the same amount of examples. A balanced data set allows a model to learn equal amounts of characteristics from each one of the classes...

Hyperparameter

Written by Evispot. Posted in Glossary, h.

Hyperaparameter is a parameter whose value is used to control the learning process of a specific AI model. A hyperparameter has to be set / fixed before starting the training process.

Cross validation

Written by Evispot. Posted in c, Glossary.

To assess how a model will perform in practice we need to validate it against an independent data set. This is commonly done by splitting the data into training and test set. A model is then trained on the training set and validated on the test set....

Out-of-time Test

Written by Evispot. Posted in Glossary, o.

Out-of-time test is the method of training a model on data from the earlier part of the time-interval and testing it against the later, so called out-of-time test set. The purpose is to create a testing scenario where the model and test set simulates...

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