From 72751502570de0a15c631785d887b03b108bf834 Mon Sep 17 00:00:00 2001 From: Ivo Facoco Date: Thu, 21 Nov 2024 12:36:29 +0000 Subject: [PATCH] fix: formatting errors in documentation --- docs/index.md | 2 +- docs/installation.md | 6 ------ 2 files changed, 1 insertion(+), 7 deletions(-) diff --git a/docs/index.md b/docs/index.md index 60df317..5e0f4fc 100644 --- a/docs/index.md +++ b/docs/index.md @@ -7,7 +7,7 @@ real and synthetic datasets across image, tabular, and time-series data modaliti developed to address gaps in existing evaluation frameworks that either lack metrics for specific data modalities or do not include certain state-of-the-art metrics. The library is designed to be modular, allowing users to easily extend it with new metrics. -The source code is available on [GitHub](https://github.com/fraunhoferportugal/pymdma/tree/main) and the documentation can be found [here](dummy). +The source code is available on [GitHub](https://github.com/fraunhoferportugal/pymdma/tree/main). ## Metric Categories Each metric class is organized based on the modality, validation type, metric group and goal. Following is a brief description of these categories: diff --git a/docs/installation.md b/docs/installation.md index b1c52fb..5521a12 100644 --- a/docs/installation.md +++ b/docs/installation.md @@ -6,12 +6,6 @@ PyPI is currently unavailable. To install the package, you can install it direct $ pip install "pymdma @ git+https://github.com/fraunhoferportugal/pymdma.git" ``` - - Depending on the data modality you are working with, you may need to install additional dependencies. We have three groups of denpendencies: `image`, `tabular` and `time_series`. As an example, to work with image data, you will need to run the following command: ```bash