fix image paths

JaredSchwartz · Aug 10, 2024 · 0d1b705 · 0d1b705
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diff --git a/.github/logo.png b/.github/logo.png
diff --git a/README.md b/README.md
@@ -1,5 +1,5 @@
 <p align="center">
-<img width="400px" src="./docs/src/assets/logo.svg" title="RuleMiner.jl logo"/>
+<img width="400px" src=".github/logo.png" title="RuleMiner.jl logo"/>
 </p>
 
 # RuleMiner.jl - Association Rule Mining in Julia

diff --git a/docs/src/closed_itemsets.md b/docs/src/closed_itemsets.md
@@ -1,6 +1,6 @@
 # Closed Itemset Mining
 
-![Diagram showing maximal itemsets as a subset of closed itemsets which are a subset of frequent itemsets](./assets/closed.png)
+![Diagram showing maximal itemsets as a subset of closed itemsets which are a subset of frequent itemsets](assets/closed.png)
 ## Description
 
 Closed itemset mining is a set of techniques focused on discovering closed itemsets in a transactional dataset. A closed itemset is one which appears frequently in the data (above the minimum support threshold) and which has no superset with the same support. In other words, closed itemsets are the largest possible combinations of items that share the same transactions. They represent a lossless compression of the set of all frequent itemsets, as the support of any frequent itemset can be derived from the closed itemsets. 

diff --git a/docs/src/frequent_itemsets.md b/docs/src/frequent_itemsets.md
@@ -1,6 +1,6 @@
 # Frequent Itemset Mining
 
-![Diagram showing maximal itemsets as a subset of closed itemsets which are a subset of frequent itemsets](./assets/frequent.png)
+![Diagram showing maximal itemsets as a subset of closed itemsets which are a subset of frequent itemsets](assets/frequent.png)
 ## Description
 
 Frequent itemset mining is a fundamental technique in data mining focused on discovering itemsets that appear frequently in a transactional dataset. A frequent itemset is a set of items that occurs together in the data with a frequency no less than a specified minimum support threshold. Frequent itemsets form the basis of various data mining tasks, including association rule mining, sequential pattern mining, and correlation analysis.