Confusion Matrix

A confusion matrix helps to illustrate what kinds of errors a classification model is making. If you have a binary classifier model that distinguishes between a positive and a negative class, you can define the following 4 values depending on the...

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Cross validation

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....

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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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Capital Cover Rate

Capital Cover Rate or Capital Adequacy Ratio (CAR) is a measurement of a bank’s available capital expressed as a percentage of a bank’s risk-weighted credit exposures. The capital adequacy ratio, also known as capital-to-risk weighted...

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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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