Update README.md

README.md

@@ -37,17 +37,16 @@ Breast_Cancer_Histopathological_Dataset/
 - **Image Data**: Each file contains a histopathological image of breast cancer tissue.
 - **Classes**: There are two classes, each represented by a separate folder based on the type of tissue (benign or malignant).
 
-## Usage
+## Usage (not pre-split; optimal parameters)
 Here is an example of how to load the dataset using PrismRCL:
 
 ```
-C:\PrismRCL\PrismRCL.exe chisquared rclticks=10 boxdown=0 data=C:\path\to\Breast_Cancer_Histopathological_Dataset\train_data testdata=C:\path\to\Breast_Cancer_Histopathological_Dataset\test_data savemodel=C:\path\to\models\mymodel.classify log=C:\path\to\log_files stopwhendone
-```
+C:\PrismRCL\PrismRCL.exe fractal imaginary rclticks=15 boxdown=0 channelpick=4 data=C:\path\to\Breast_Cancer_Biopsy_7500 testsize=0.1 savemodel=C:\path\to\models\mymodel.classify log=C:\path\to\log_files stopwhendone```
 
 Explanation:
 - `C:\PrismRCL\PrismRCL.exe`: classification application
 - `chisquared`: training evaluation method
-- `rclticks=10`: RCL training parameter
+- `rclticks=15`: RCL training parameter
 - `boxdown=0`: RCL training parameter
 - `data=C:\path\to\Breast_Cancer_Histopathological_Dataset\train_data`: path to training data
 - `testdata=C:\path\to\Breast_Cancer_Histopathological_Dataset\test_data`: path to testing data