# Calculator

## Precision Recall Calculator (simple to use) Paid Members Public

Precision and recall are metrics for classification machine learning models. Recall is the model's ability to capture positive cases and precision is the accuracy of the cases that it does capture.

## Confusion Matrix Maker (simple to use) Paid Members Public

The confusion matrix is a set of four values which show the performance of classification machine learning models per class. These four values are True Positive, False Positive, True Negative, and False Negative.

## Confusion Matrix Calculator (simple to use) Paid Members Public

The confusion matrix is a method of measuring the performance of classification machine learning models using the True Positive, False Positive, True Negative, and False Negative values. These four values can be used to calculate a set of metrics that describe different aspects of model performance.

## MAE Calculator (Mean Absolute Error) Paid Members Public

MAE (Mean Absolute Error) is a common metric to use for measuring the error of regression predictions. Use this calculator to calculate the MAE for a list of predictions and their corresponding actual values.

## Coefficient of Determination Calculator (simple to use) Paid Members Public

The Coefficient of Determination, often called R Squared, is a metric that measures a model's goodness of fit, and the Correlation Coefficient (often called R) is the correlation between the two sets of values. This calculator will calculate both these metrics for two data lists.

## R Squared Calculator (Both R and R2) Paid Members Public

R Squared (R2) is a metric that measures a model's goodness of fit, and R is the correlation between the two sets of values. This calculator will calculate both R and R-Squared values for two data lists.

## Accuracy Calculator (accuracy percentage) Paid Members Public

Accuracy is a common metric to use for measuring the error of classification predictions. There are several ways to calculate the accuracy percentage, in this post you will find the two most common ways of doing so.

## MAPE Calculator (Mean Absolute Percentage Error) Paid Members Public

MAPE (Mean Absolute Percentage Error) is a common metric to use for measuring the error of regression predictions. Use this calculator to calculate the MAPE for a list of predictions and their corresponding actual values.