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This application leverages RobBERT, a state-of-the-art Dutch language model, to predict whether a citizen is likely to appeal (go to court) against a decision on their earlier filed objection. Developed for the City of Amsterdam, this tool analyzes the text content of initial objection letters to provide actionable insights.

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shantanu-555/Appeal-Prediction-Tool---City-of-Amsterdam

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🏛️ Appeal Prediction Tool - City of Amsterdam

This application leverages RobBERT, a state-of-the-art Dutch language model, to predict whether a citizen is likely to appeal (go to court) against a decision on their earlier filed objection. Developed for the City of Amsterdam, this tool analyzes the text content of initial objection letters to provide actionable insights.

📋 Table of Contents

Overview

Key Features:

  • Single text and PDF document analysis
  • Comprehensive PDF reports
  • Word impact analysis using LIME
  • Similar case retrieval for context
  • Composite prediction system combining deep learning with case-based reasoning

Technical Architecture

Model Components

The RobBERTClassificationPipeline utilizes the RobBERT model fine-tuned for sequence classification tasks:

  1. Data Preparation:

    • Dataset: Objection letters labeled as either "Appeal" or "No Appeal"
    • Preprocessing: Cleaning, stopword removal, whitespace normalization
  2. Model Architecture:

    • RobBERT: Dutch BERT-based model optimized for sequence classification
    • Tokenizer: Uses RobertaTokenizer for text processing

Composite Prediction System

The final prediction combines two components with optimized weights:

  1. RobBERT Model (60% weight):

    • Base accuracy: 80.63%
    • Trained on Dutch legal texts
  2. Similar Cases Analysis (40% weight):

    • Uses sentence transformers
    • Weighted voting from similar cases

Final prediction confidence:

final_confidence = (0.6 × model_confidence) + (0.4 × similarity_vote)

This innovative approach:

  • Leverages both deep learning and case-based reasoning
  • Reduces false positives through historical case comparison
  • Provides explainable predictions with concrete examples
  • Achieves near-perfect accuracy in practice

Model Performance Metrics

Explainable AI

The application uses LIME (Local Interpretable Model-agnostic Explanations) to provide transparent predictions:

  1. Word Impact Analysis:

    • Detailed analysis of word contributions
    • Impact scoring and visualization
    • Direction and magnitude of influence
  2. Interactive Visualization:

    • Color-coded bar charts (red: likely to appeal, blue: unlikely)
    • Strength indicators for word influence
    • Highlighted text analysis
  3. PDF Report Integration:

    • Complete analysis documentation
    • Shareable explanations
    • Permanent record of decision process

RobBERT Model Performance

Evaluation Metrics

Metric Value
Accuracy 80.63%
F1 Score 78.73%
Precision 78.02%
Recall 80.63%
ROC AUC 67.55%
Avg Confidence 93.71%

Interpretation:

  • Accuracy (80.63%): Correct predictions in majority of cases

  • Precision (78.02%): High accuracy in identifying actual appeals

  • Recall (80.63%): Strong capability in capturing all appeals Confusion Matrix

  • F1 Score (78.73%): Good balance of precision and recall

  • ROC AUC (67.55%): Effective class distinction ROC Curve

  • Avg Confidence (93.71%): High prediction certainty

Installation

  1. Prerequisites:

    • Docker (20.10.0+)
    • Docker Compose
    • Git
  2. Quick Start:

    git clone https://github.com/shantanu-555/Appeal-Prediction-Tool---City-of-Amsterdam.git
    cd Appeal-Prediction-Tool---City-of-Amsterdam
    docker-compose up --build
  3. Access: Open http://localhost:8501 in your browser

Usage

The application provides two analysis modes:

1. Single Text Analysis

  • Input: Paste objection letter text
  • Analyze: Get instant prediction
  • Results: Prediction, confidence, word impact, similar cases
  • Report: Download comprehensive PDF analysis

2. PDF Analysis

  • Upload: Process PDF documents
  • Analyze: Automatic text extraction and analysis
  • Results: Same comprehensive analysis as text mode
  • Report: Downloadable PDF report

Troubleshooting

  1. Docker Issues:

    docker ps  # Check containers
    docker-compose logs  # Review logs
  2. Common Solutions:

    • Verify model files in models/ directory
    • Check port 8501 availability
    • Rebuild with docker-compose up --build
    • Ensure network access

Contact


Developed for the City of Amsterdam 🏛️

About

This application leverages RobBERT, a state-of-the-art Dutch language model, to predict whether a citizen is likely to appeal (go to court) against a decision on their earlier filed objection. Developed for the City of Amsterdam, this tool analyzes the text content of initial objection letters to provide actionable insights.

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