| ... | ... |
@@ -1,6 +1,6 @@ |
| 1 | 1 |
# ClassifyR: Performance evaluation for multi-view data sets and seamless integration with MultiAssayExperiment and Bioconductor |
| 2 | 2 |
|
| 3 |
-<img src="inst/ClassifyRsticker.png" align="right"> |
|
| 3 |
+<img src="man/figures/ClassifyRsticker.png" align="right" width=250 style="margin-left: 10px;"> |
|
| 4 | 4 |
|
| 5 | 5 |
ClassifyR's performance evaluation focuses on model stability and interpretability. Based on repeated cross-validation, it is possible to evaluate feature selection stability and also per-sample prediction accuracy. Also, multiple omics data assays on the same samples are becoming more popular and ClassifyR supports a range of multi-view methods to evaluate which data view is the most predictive and combine data views to evaluate if multiple views provide superior predictive performance to a single data view. |
| 6 | 6 |
|
