Author: Evispot

Mean Squared Error (MSE)

The MSE metric measures the average of the squares of the errors, that is  the average squared difference between the estimated values and the actual value. The MSE is a measure of the quality of an estimator—it is always non-negative, and values...

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Log loss

Log loss, also called logistic regression loss or cross-entropy loss, is defined on probability estimates.The metric looks at how well a model can classify a binary target, log loss evaluates how close a model’s predicted values (uncalibrated probability...

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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...

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ROC curve

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...

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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...

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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.

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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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