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Update README.md

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@@ -12,7 +12,6 @@ An updated version of Standard-Based Impact Classification (SBIC) method of CSR
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  Instructions on how to run the code below.
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- ---
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  # **Multilabel Classification Step**
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@@ -57,7 +56,7 @@ The script follows these main steps:
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  2. **Perform Cosine Similarity Search**: Finds the most relevant reports (sentences) using `semantic_search` from `sentence-transformers`.
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  3. **Apply K-Nearest Neighbor (KNN) Algorithm**: Selects top similar reports (sentences) and aggregates predictions.
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  4. **Use Sigmoid Activation for Classification**: Applies a threshold to generate final classification outputs.
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- 5. **Save Results**: Exports `df_results_0_50k.csv` containing the processed data for the first 50k of records.
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  ## **Output File**
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  Instructions on how to run the code below.
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  # **Multilabel Classification Step**
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  2. **Perform Cosine Similarity Search**: Finds the most relevant reports (sentences) using `semantic_search` from `sentence-transformers`.
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  3. **Apply K-Nearest Neighbor (KNN) Algorithm**: Selects top similar reports (sentences) and aggregates predictions.
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  4. **Use Sigmoid Activation for Classification**: Applies a threshold to generate final classification outputs.
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+ 5. **Save Results**: Exports `df_results_0_50k.csv` containing the processed data for the first 50k of records.
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  ## **Output File**
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