--- title: what is the difference between True Positive, True Negative, False Positive – Type 1 Error and False Negative – Type 2 Error? description: what is the difference between True Positive, True Negative, False Positive – Type 1 Error and False Negative – Type 2 Error? --- [Skip to content](https://help.datasciencedojo.com/migration/what-is-the-difference-between-true-positive-true-negative-false-positive-type-1-error-and-false-negative-type-2-error#main-content) English Show submenu for translations [Customer portal](https://help.datasciencedojo.com/tickets-view?hsLang=en) ![DSD main logo.png\]](https://help.datasciencedojo.com/hs-fs/hubfs/DSD%20main%20logo.png?height=40&name=DSD%20main%20logo.png) - [Default HubSpot Blog](https://help.datasciencedojo.com/blog) Open main navigation Close main navigation - [Default HubSpot Blog](https://help.datasciencedojo.com/blog) - English Show submenu for translations - [Customer portal](https://help.datasciencedojo.com/tickets-view) - Go to datasciencedojo.com Go to datasciencedojo.com How can we help? - There are no suggestions because the search field is empty. 1. [Help Center](https://help.datasciencedojo.com/migration?hsLang=en) 2. [Machine Learning](https://help.datasciencedojo.com/migration/machine-learning?hsLang=en) # what is the difference between True Positive, True Negative, False Positive – Type 1 Error and False Negative – Type 2 Error? Type I error is committed when the null hypothesis is true and we reject it, also known as a ‘False Positive’. Type II error is committed when the null hypothesis is false and we accept it, also known as ‘False Negative’.   In the context of confusion matrix, we can say Type I error occurs when we classify a value as positive (1) when it is actually negative (0). 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