Update README.md

README.md

@@ -37,22 +37,21 @@ Ecommerce_Product_Descriptions/
 
 ## Usage (not pre-split; optimal parameters)
 Here is an example of how to load the dataset using PrismRCL:
-
 ```bash
 C:\PrismRCL\PrismRCL.exe chisquared rclticks=65 boxdown=8 channelpick=5 data=C:\path\to\Ecommerce_Product_Descriptions_mm 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=65`: RCL training parameter
-- `boxdown=8`: RCL training parameter
-- channelpick=5 : RCL training parameter
-- `data=C:\path\to\Ecommerce_Product_Descriptions\train_data`: path to training data
-- `testdata=C:\path\to\Ecommerce_Product_Descriptions\test_data`: path to testing data
-- `savemodel=C:\path\to\models\mymodel.classify`: path to save resulting model
-- `log=C:\path\to\log_files`: path to logfiles
-- `stopwhendone`: ends the PrismRCL session when training is done
+Explanation of Command:
+- `C:\PrismRCL\PrismRCL.exe`: Path to the PrismRCL executable for classification
+- `chisquared`: Specifies Chi-squared as the training evaluation method
+- `rclticks=65`: Sets the number of RCL iterations during training to 65
+- `boxdown=8`: Configuration parameter for training behavior
+- `channelpick=5`: RCL training parameter
+- `data=C:\path\to\Ecommerce_Product_Descriptions_mm`: Path to the complete dataset for Ecommerce Product Descriptions classification
+- `testsize=0.1`: Specifies that 10% of the data should be used for testing
+- `savemodel=C:\path\to\models\mymodel.classify`: Path to save the resulting trained model
+- `log=C:\path\to\log_files`: Directory path for storing log files of the training process
+- `stopwhendone`: Instructs PrismRCL to end the session once training is complete
 
 ## License
 This dataset is licensed under the Creative Commons Attribution 4.0 International License. See the LICENSE file for more details.