Data Mining Method Selector Data Mining Method Selector AI-powered decision intelligence platform for optimal data mining methodology selection Confidence Score –% Methods Analyzed — Match Quality — Complexity — Est. Timeline — 1. Primary Objective šÆ Predict Outcomes Forecasting & regression š Classify Data Categorization tasks š® Discover Segments Unsupervised clustering š Pattern Mining Association rules ā ļø Anomaly Detection Outlier identification š Sequence Analysis Temporal patterns 2. Data Characteristics š Structured Tables Rows & columns š Text Corpus Documents & NLP ā° Time Series Temporal sequences š Transactions Market basket data š Multi-modal Mixed types 3. Label Availability ā Fully Labeled Supervised learning šø Partial Labels Semi-supervised ā Unlabeled Unsupervised 4. Dataset Scale š Small Scale < 10K records š¦ Medium Scale 10K – 1M records šļø Large Scale > 1M records 5. Explainability Requirements š Critical Regulatory/compliance š Preferred Nice to have š¤ Not Required Black box acceptable š Generate Intelligence Report Executive Summary Recommended Methodologies Comparative Performance Analysis Implementation Roadmap