Variable selection

Adding variables to your data set can improve the accuracy of your AI model, especially when the model is too simple to fit the existing data properly. However, it is important to focus on variables that are relevant to the problem you’re trying to...

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Variable engineering

Variable engineering is the secret weapon that advanced data scientists use to extract the most accurate results from algorithms. Evispot AI platform employs a library of algorithms and variable transformations to automatically engineer new, high...

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Categorical variables

A categorical variable is an input variable that has a discrete set of possible values. For example, if your variable is ‘season’ the possible values it can take are ‘Winter’, ‘Spring’, ‘Summer’ and ‘Autumn’.

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Feature

A feature is an input variable. It can be numeric or categorical. For example, a house can have the following features: number of rooms (numeric), neighbourhood (categorical), street name (categorical).  The term “variable” throughout the Evispot...

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Shapley value

Shapley explanations are a technique with credible theoretical support that presents consistent global and local variable contributions. Local numeric Shapley values are calculated by tracing single rows of data through a trained tree ensemble and...

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Swap-out

Swap-out is a previously accepted loan which with the newly develop model and/or setting will be denied. SInce the swap-out previously was accepted is an actual label available.

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Machine learning in credit decisions

Leveraging machine learning for smarter lending and obtain insights into the technology behind 100% transparent machine learning models.

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