Detect Data Problems
Before Your Model Fails.

DatasetDoctor helps ML engineers and data scientists Detect leakage, missing values, outliers, and ML risks before training your model.

DatasetDoctor Mobile Interface Preview

Data Quality Score (DQS)

Our proprietary weighted heuristic measures statistical health, feature sparsity, and distribution reliability at the schema level.

PROPRIETARY METRIC

Core Audit Suite

Modular plugins designed to separate signal from noise.

Statistical Moments

Deep analysis of mean, variance, skewness, and kurtosis.

ML Readiness

Checks whether your dataset is ready for ML training.

Duplication Check

Detect duplicate and repeated records instantly.

Class Imbalance

Real-time detection of target label distribution skew.

Outlier Detection

Automated Z-score and IQR anomaly isolation.

Feature Cardinality

Detects high-variance categorical overhead.

Predictive Power Signal

Uses Mutual Information (MI) to detect data leakage and separate signal from noise.

🔥 Leakage 💎 Strong ⚡ Moderate ☁️ Noise

AI Smart Suggestions

Context-aware recommendations for feature engineering, encoding strategies, and data enrichment based on column semantics.

Basic Cleaning

  • Smart Imputation
  • Deduplication
  • Type Casting

System Architecture

V3.0 CORE
Data Ingest
Source Connectors CSV / JSON / SQL
Intelligence Engine
Core Inspector Orchestration & Registry
Plugins
Audit
Clean
Presentation
Intelligence UI Reactive Overlays & Insights