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Group similar data points together without labels. Discover hidden patterns, segment customers, detect anomalies, and explore the natural structure in your data.
14
Algorithms
4
Categories
Algorithms
Train models to predict categorical labels from features. Build classifiers with confusion matrices, ROC curves, feature importance, and calibration diagnostics.
9
Algorithms
4
Categories
Algorithms
Predict continuous numeric values from features. From linear baselines to gradient boosting — with R², residual plots, and feature importance diagnostics.
11
Algorithms
4
Categories
Algorithms
Preprocessing
Data Preparation
Clean, transform, and encode datasets through a sequential Transformation Chain. Impute missing values, scale features, encode categoricals, and filter columns — then export to Pipeline or Python.
Dim. Reduction
Transformation & DR
Reduce high-dimensional data for visualization, noise removal, and feature extraction. From classic PCA to modern manifold techniques like UMAP and t-SNE.
Genetic Algos
Optimization
Evolutionary optimization algorithms inspired by natural selection. Solve complex search and optimization problems with population-based metaheuristics.
Time Series
Forecasting
Forecast future values from sequential data. ARIMA, Prophet, exponential smoothing, and deep learning approaches for temporal patterns.
Assoc. Rules
Market Basket
Discover item co-occurrence patterns in transactional data. Find which products are frequently bought together using Apriori and FP-Growth.
Pick from Clustering, Classification, Regression, Preprocessing, or Dimensionality Reduction — or build a Pipeline.
Upload a CSV or Excel file, pick an algorithm, tune parameters, and hit run — or chain steps in Pipeline mode.
Explore interactive charts, detailed metrics, and downloadable model files. All results are visual and exportable.
60+
Algorithms & Methods
6
Modules
N-D
Dimensional Support
CSV / XLSX
Data Upload